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Yes, Ami, the floor is yours. 10 to 10 to 12 min. Will you give me a sign on time?

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OK, great. Thank you so much for having me here today. Thank you for the organizers and thank you to everyone who came out on a Saturday afternoon at the end of the conference.

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I'd like also like to extend my respect to the Rowentary people who succeeded. Sure.

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Sure, whose unseated lamb we're sitting on today and extend my respect to any Aboriginal or Tor Strait Island people here today.

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So my presentation is about understanding how laws and policies contribute to the economic gender gap. All of the data I'll be sharing here today comes from a book Equality Within Our Lifetimes, how laws and policies can close or widen gender gaps in economies worldwide.

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This is an open access book, so freely downloadable and all of the data I'll be sharing is.

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Public use data available on our website interactive. You can also download share the maps and interactive graphics.

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The motivation for writing this book was really our shared understanding that we we hear all of these grim statistics that it will be hundreds of years to achieve gender equality.

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But what's often lacking from the conversation is just the understanding that gender equality is often embedded in our illegal frameworks.

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It's embedded in gender discriminatory laws by laws that don't reflect gender experiences by laws that ignore unpaid care work that perpetuates gender inequality in care and in work.

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So this book was really an attempt to look systematically across all 193 UN member states where the gaps are in these laws where we're doing well and understand where there's been progress and what are feasible models for improving the legal framework as a first step to really improving the lived experiences of women and girls.

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Just a brief overview of the methodology and I'm happy to go into more detail later.

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All of the legal data you'll see presented here today is based on a review of original constitutional text, legislation, and policy documents.

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So we had a multidisciplinary multilingual team of policy researchers reading through legislation in full, answering questions about it.

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2 researchers would read it independently. And then reconciled their answers to try and ensure a high level of data quality.

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We then meet as a team to review any cases where they couldn't come to an agreement and then go through a really rigorous series of data quality and checks.

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So I'm gonna go through pretty quickly just to give you a sense of the range of ways that laws can perpetuate or help achieve gender equality and economies.

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Obviously for any of these areas we could spend a whole presentation just on that single legal area but I want to give you just a flavor of the range of areas we cover.

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Some of these are laws directly targeting gender discrimination at work. Nearly every country in the world has along the books prohibiting gender discrimination at work.

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88% of countries prohibit gender discrimination and pay. Many of these are actually really strong guarantees of equal work for equal value.

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But where the real gaps are are on training and advancement. And equal right to promotion. So maybe it's not surprising that where women's economic opportunism, these really fall short is when we get to positions of leadership.

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That's where the legal protections are really lacking in many countries. When we think about equality at work, it really needs to mean equality at work for all women.

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Have countries taken that first step of ensuring legal gender equality. For based on intersectional categories. So this is a bit hard to read in the room.

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But those first 3 lines as our religion and gender, race and gender, disability and gender. These are very well-covered areas.

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Less well-covered are age social class foreign national origin and we know these often intersect they're often intertwined but they're not as well covered and at the very bottom perhaps not surprising sexual orientation and gender identity receiving much less protection globally.

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Of course we know that caregiving discrimination is hard to separate from gender discrimination in many countries. What we see is a gender pay gap is really a motherhood penalty.

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While 93% of countries have at least some protection from gender discrimination at work, only half have protections for mothers from caregiving discrimination at work.

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And you'll see only 2 thirds a little more than two-thirds do it for pregnancy and again once you get into this the details really matter most of those pregnancy provisions are around terminations.

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They're not around enabling pregnant women to continue to advance their careers during pregnancy.

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So that's just a sense of the range of the gaps that we see in these laws that are meant to directly prohibit discrimination at work.

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The laws also need to have implementation measures in them ways to ensure that women have pathways to access justice.

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So just due to time I haven't gone deep into the details we have on sexual harassment laws. But we know that even if there's a sexual harassment law on the books If there aren't provisions ensuring that women are protected from retaliation for reporting sexual harassment, they're not likely to do so.

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And as you can see, All of, much of the world, the majority of the world has gaps.

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In laws to protect women from retaliation when we're reporting it, the court of the world still hasn't even gotten around to legally banning sexual harassment at work.

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We also see major gaps in access to alternative dispute resolution mechanisms, access to justice, of course the cost of litigation is a major barrier.

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This is before we even get to questions like are these independent commission's funded well enough? Do are women aware of them?

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You know, can they even get to them? At a presentation with someone from Amnesty who was saying in Africa only about half of the human rights commissions even have a location outside of the capital city and they don't have an online mechanism.

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So there's both implementation issues in many countries, but there's also these legal gaps where there's not even those.

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Rights to seek justice written into the law itself.

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And then of course coming back to unpaid care, even before the pandemic the ILO estimated that there were 606 million women out of the workforce due to uncompaid care compared to 41 million men.

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The majority of the world has guaranteed at least some paid leave for mothers. Of infants, it matters to women's economic opportunities, it matters to infant.

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Health far, far less for fathers. Why does that matter to gender equality at work? We're not going to solve the care gap if we don't also support men's rights to be equal caregivers from the start.

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The research is really strong that engaging men in caregiving and infancy helps set those equal roles. From early childhood that then persists that matters for gender equality and caregiving that matters for women's physical and mental health that matters for gender equality at work.

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The good news is with this data and we can show this across a wide range of areas, we are seeing significant change over time.

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So if we go back to 1,995 to the Beijing platform for action we can see that paid leave for fathers has increased threefold.

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In countries, but it's still not enough.

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And another large gap in unpaid care is of course what what happens beyond infancy? Well, children go to school, but children still go, it gets sick.

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The pandemic really highed these care needs that persist beyond infancy that I think had largely been invisible.

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We're told to keep our kids home. Whenever they have a fever now but of course few countries actually support that with paid leave and it's women who predominantly stay home when children are sick.

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And for children, serious health needs often it's too short to really. Support the care needs that they have.

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And as the global economy is or as the global population really ages, another serious consideration is elder care needs.

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There's even less support for elder care. Needs and caregiving than there is for children's caregiving needs as this map shows and when that support is available it's often very short.

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The duration of paid leave here as you're seeing on this map really isn't enough to support end of life care unless you have a lot of caregivers.

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Engaged and again this is something that for many women is coming when they're just reaching their career potential, right?

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They're reaching that transition to position of leaderships. So this again helps to explain why we may not see women making that transition as much to positions of leadership.

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If they're having to choose between elder care responsibilities. And their career.

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And I just included briefly and I won't go into these just because of time some examples of how this evidence has been used by both policymakers and civil society.

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So having the quantitative data does enable countries and policy makers to really see what's feasible to see where they stand.

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In the global comparison. It also enables really rigorous analysis of the impact that policies have on outcomes.

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So here, policymakers in the Philippines use both where they stood in the global context. As well as research that we had done.

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Rigorously showing the impact that paid leave had on infant mortality rates that paid leave actually lowered mortality to build the investment case for investing in caregiving.

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It's also been used by civil society organizations. So for the twentieth anniversary of the Beijing platform for action, equality now came to us.

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They wanted to do a report on gender inequality embedded in laws. They wanted to make sure that they weren't.

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Only highlighting low income countries that they had geographic diversity in their reports so they asked us for a good high-income country example, a good European example in particular.

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Of gender inequality embedded in law. We mentioned to them Ireland only had at the time paid leave available for mothers of infants.

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Fathers couldn't take any paid leave. And that began a campaign where Ireland went on to pass.

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2 weeks of paid leave for fathers. Since then they've substantially increased their paid leave and Ireland is now no longer a laggard in Europe for paid leave for fathers is actually I think they're at 7 or 9 weeks for paid leave for fathers which is putting it more in line with It's peers.

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So this is, you know, data that can be used to push for change. All of the data I've shared is available in the book but also on our website world policy center.

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E and we very much welcome ways of exploring. We can how we can work together. Thank you.

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Thank you so much. So we are moving to our second presenter. So we will keep all the questions till the end of the session, please.

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Aha. Yeah, after all the presenters will speak. So please a second presenter, gender occupational segregation and wage gaps in the policies.

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So please, Neil. Thank you. Excuse me. Thank you very much.

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And I think in many ways, my presentation flows very well from the fantastic overview of the global situation from before but also raises some mixed feelings as a Canadian were on the one part from the global perspective we scored pretty high on paper.

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We're often among those. Oh yes we have guaranteed paid paternity we have this we have that we have protections and yet to our knowledge this study is the first empirical investigation.

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Of those at the center of actually providing the evidence to inform those very gender responsive policies. We looked specifically at the gender situation with regard to a policy research workforce in Canada.

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Ational segregation, gendered page, pay gaps, women around the world, including in high-income countries systematically earn less than men.

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The OECD estimate is for high income countries, women earn about 77 cents for every dollar earned by men.

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And in particular, our background to this piece of work comes from the global health workforce and particularly the WHO landmark report from 2,019 that the health care sector is one that is delivered by women and yet led by men.

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Within Canada, the health workforce and like most countries around the world, exacerbated by the COVID pandemic issues of health workforce shortages, burnout imbalances are gaining more political traction.

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It is a highly feminized workforce as well, nearly 80% of those in health and social care occupations are estimated to be women.

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Yet in Canada in part perhaps because of methodological issues in our decentralized health care systems. We have very few national level data sets that allow us to compare across provinces and territories on issues.

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And perhaps resistance to even admitting that gender wage gaps exist and need to be admitting that gender wage gaps exist and need to be addressed.

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Highly educated health care occupations. The idea that this is a field that is driven by evidence perhaps leads to a certain resistance to admitting that you know some of these structures may in and of themselves be uninentionally exacerbating gender disparities.

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And in particular, while we're seeing increasing interest and research on clinical health care professions such as the medical field such as nursing very very few national studies look at non-clinical health professionals.

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Those who don't necessarily provide direct patient care but are critical to health system performance including health policy researchers.

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So that was our our background to dive into looking at gender composition and wages in the health policy research workforce in comparison to other both traditionally female dominated as well as traditionally male-dominated policy research.

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Areas or fields of application. Our underlying hypothesis was driven by the notion that societal devaluation of women's work persists.

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And that's despite an influx of women into many previously male-dominated professions, including policy research.

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We were guided by the notion that sectors themselves are social constructs. Why is it? And this was expected and this was actually raised by one of the peer reviewers to our manuscripts submission to an academic journal, well of course economists are going to be paid higher than health policy researchers.

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Without questioning, why do we assume that? It's a social construct. And I think the previous speaker mentioned the idea about pay equity policies.

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So Canada certainly has had decades of experience with the notion of equal pay for equal work and yet we need to be moving beyond that to the notion of Equal pay for work of Comparable value.

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And so this is where our research takes that notion. Where we use nationally standardized population census data and targeted those university education policy researchers as Matt systematically to the National Occupational Classification and in particular within the same statistical minor group means that positions in this category should have the same levels of specialist

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training. Working conditions and on the job responsibilities. In other words, theoretically there should not be any rationale for why people within the same group Experience wage disparities compared to others with similar skill levels and working conditions.

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And in particular, our identification including those whose jobs were described as specializing in research and analysis to support the development, administration, and evaluation of policies and programs, whether in government or non-government, which inherently include those gender responsive.

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Policies in and of themselves as the main duties of their job. I won't mention here this does not include academic based researchers.

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So we looked at gender composition, gender wage gaps, which in our census was captured through objectively measured data from linked administrative income tax and benefit records.

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And we used gender as our main explanatory variable, for the usual suspects in terms of human capital variables and including many of the usual suspects in terms of intersecting social identity variables.

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And we used Sort of. Typical econometric methods in terms of log linear regressions and Blindro-huxana decomposition methods.

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So. The policy research workforce itself. Councillor B 120, Canadian workers in their prime.

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Working years. So what did we find? So in this workforce itself about 60% are women and yet that balance changes depending on how policy researchers are applying their knowledge and skills to what domain.

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Ranging from about 75% and skills to what domain? Ranging from about 75% in the health and skills to what domain, ranging from about 75% in the health and economic health health at education policy domains.

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Traditionally, female dominated. Workforces in general as well down to about half in natural not applied science policy applications and 44% in economics policy applications.

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So this is Economics was the only male dominated field of application.

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And then what did we find? Well, you know what? Similar. Skills, similar job responsibilities, those in economics earned more than those in traditionally, those it not traditionally but currently female dominated fields of policy application and this was the true for both women and for men and you know what The higher the percentage of women

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with in that policy application. The lower the salaries. 4 women and even faster for men. An implication?

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Health and education are penalized in terms of being able to attract and retain top talent in Equitable oriented policy research.

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Similar job descriptions, responsibilities, and duties. So we thought so. Not all the peer reviewers did, but we thought so.

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So we also did the Waxana, the Waxa, Wahaka blinder decomposition method.

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We did long linear and multiple regressions against the pool of health policy and other non-health policy researchers.

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Perhaps not surprisingly, women earned less than men after controlling for the full set of personal and professional characteristics.

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Even about 4 to 5% less in health and social policy research up to 11 to 12% less in science and business policy research.

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And in the decomposition method we found that much of the wage gap. Was unexplained by the measured predictors by the structural differences between men between the male policy research workforce and the female.

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Often attributed in the literature to an unmeasured effect of gender bias and discrimination.

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So what are some of the policy implications of our work? So as mentioned we conducted a systematic Search for literature and were unable to find any other studies.

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Part of this might be related to many national occupational classifications and in particular the ILOs international standard classification doesn't distinguish different fields of application.

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The ISCO just has policy administration researchers as one. So it it minimizes opportunities for cross-national research on this specific workforce subgroup.

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We believe though that many of these wage gaps are inherently sociologically, psychologically being fueled by remuneration structures that favor male-dominated fields over female dominated fields.

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For purely sociological. Social reasons of social construct. This was based I might add on 2,016 census data we're looking our day 2,021 census data just became available last week for research use so as soon as I get back to Canada we're going to start looking at the new data and seeing whether some

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of these The impacts have been widened by the COVID pandemic largely believed for clinical health workers very little evidence on non-clinical health workers.

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And so, I mean, I could go on, but. I won't. So thank you.

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Thanks to my co-authors and for those who are interested, we did have the full study published and I believe it's also on the Congress app you can download the full paper now as well otherwise the DOI is there.

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Thank you.

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Thank you very much for a very informative presentation. I think it was very interesting. So please try to keep all your questions until we listen to the last presentation.

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So the next presentation is about inequality and construction trades training through gender transformative pedagogy.

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Okay.

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So should be, yes please. Because you have a lot of co-workers, you want

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Thank you, Tiana. Friends, this is my first I saw. And I've been intimidated all week by everyone's very detailed papers so I apologize, I've come prepared but hopefully we can keep this quite conversational and I think Amy you've brought us to a beautiful place.

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I think really globally about the experiences of women particularly in Kind of the distinctions of women there and then Nauru thinking particularly about a highly feminized workforce in Canada.

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Let me bring you to quite a different context here in Australia thinking about a very male-dominated industry in our construction.

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Industry here. Let me just let me just paint a bit of a picture. The gender segregation in the Australian construction industry largely mirrors what we're seeing in the UK and in other OECD nations.

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Just like women. Comprising almost half of all people employed in the labor force here in Australia.

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They continue to be underrepresented in traditionally male industries and in managerial positions. And in Australia, women have consistently comprised only 2% of the field-based workers in the construction sector over the 30 the past 30 years and even when women are employed in the construction industry.

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They're often employed in less secure, low paid and ancillary roles in the sector.

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Sure. And despite significant government and industry investment, industrial gender segregation persists and women remain substantially locked out of the construction labor market.

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The gendered nature of the construction industry contributes to women's economic exclusion. And in these ways we see that vet programs and employment and construction continue to be male-dominated.

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And this research adopted Ray and Zarezky's definition of male dominated as being an industry that historically privileged educated and employed male workers.

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And the practices that are associated with traditionally male workplaces frequently influence the performance and standard of behavior towards women in these industries.

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The documented workplace cultures of prejudice in the construction industry exclude women, treating them as other. And the masculine culture enables inappropriate behavior and a culture of The existing evidence suggests that women report feeling unsafe and uncomfortable on the job.

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The overrepresentation of men in senior leadership, the gender ratio and adherence to masculine workplace cultures result in higher risk for sexual harassment in historically male industries.

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And the prevalence of unchecked masculine norms and values also enable violence, discrimination and bullying.

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And while studies of industry and the gendered practice of workers and management on construction sites has been documented, there's little qualitative evidence or research in regard to the gendered experiences of participants in the contraction trades training settings in TAFE, technical and further education settings and its relationship if there is any to the

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broader masculine culture of the construction industry. And as such, this study aimed to contribute to a meeting of this gap.

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By examining tape apprentices, trainers and managers experiences of gender in construction trade, vocational education and workplace training.

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Informed by Nelson and consistent with Ray and Zarezky the research took a critical economic feminist approach.

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Asserting that limiting access to particular industries and occupations based on a social construction of gender is a social injustice.

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There's a number of assumptions that sit beneath our research. Let me just flag that we, when we're reviewing these issues, we're viewing them in line with Holdsworth, identifying that these are systemic, they're prevalent at all levels of the construction industry.

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They significantly impact the well-being of women and they contribute to high attrition rates of women and they contribute to high attrition rates of women.

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In these training settings.

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Our study was undertaken with men and women and non-binary apprentices, teachers and training managers in one city-based Australian Taft College in a traditionally male construction trade training setting.

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Data was collected through 7 focus groups and 8 industry and stakeholder interviews. Of the total 35 participants there were 12 women, 22 men and one non-binary participant.

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The recruitment was opportunistic, it was based on availability. Participants were from various trades, both those that are licensed and unlicensed and they included apprentices, teachers and managers in plumbing, carpentry, electrical, bricklaying, electro-engineering and sign

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writing. And because of the low levels of women in these settings, we achieve saturation with women teachers and neose saturation with women apprentices.

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And we conducted a somatic analysis and initial high level themes were taken back, fed back through interviews and conversations with all of our participants to enable us to refine and validate these ideas.

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And in our interviews and our focus groups we invited participants to dialogue on their experiences of gender in a traditionally male apprenticeship workplace training setting and to reflect on their own experiences of gender equality and inequality in construction workplace learning settings in TAFE and the experiences of others that they'd observed in those settings particularly in regard to

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safety.

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And overall, the analysis found an overarching masculine culture in TAFE construction trades training that is consistent with the culture of the wider male-dominated construction industry.

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And this is as it's been described in the literature. Bye a number of others and it's also consistent with the work of Neymar and Collie and Rayan Zarezky in in vocational educational settings beyond construction.

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And so the culture was represented across a number of themes, but because we would all like to get out of here.

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Before before they close this place down. Let me just give you a bit of a snapshot of a few of these themes.

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Primary theme was around gendered spaces and women and non-binary participants described the physical, tangible expressions of the male dominated masculine culture on the TAFE workplace learning site.

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One woman a focus group participant told us. That if you walk around the TAFE campus You could do a whole portfolio of dick pics that are around.

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They are everywhere. Every book you open up there are genitals everywhere. You walk down the car door and someone's drawn a cock and bowls on cleaning equipment.

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They are in the bathrooms. It's just everywhere. And other women and non binary participants concerned, confirmed the presence of similar imagery.

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However, men apprentices, teachers and managers overlooked or minimized this conduct, indicating how gendered practices within these construction workplace cultures have become normative.

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And what the participants described is consistent with glare's observation that sexualized graffiti about partners and workmates was common in industry and it's consistent with Holdsworth's findings around how the masculine culture can be an enabler of inappropriate behaviors and can enable a work a lack of workplace support for managing

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the inappropriate behaviors in the construction industry.

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An additional sub theme was around exclusion and difference. And women are non binary participants described ways they will make made to feel other to feel excluded, unwelcome and different.

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And participants described this as being relentless and reported on the psychological and emotional toll of these gendered spaces.

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A woman teacher reported, even if it's not outright bullying, but just not feeling included in the space, feeling ostracized and on the outer.

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It's just a shit feeling. So that can definitely knock you about and knock about your confidence and make you reassess things.

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And this feeling of exclusion is consistent with the findings of Holdsworth from the construction industry beyond tape settings.

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And class suggests that this exclusion of women should be understood in the context of a systemic gendered injustice as a consequence of male behaviours.

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Self interestedly structure the practices and cultures to make these workplaces unwelcoming to women.

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An additional sub theme was around the absence of women or women being in the minority and all participants described the absence of women in their workplace learning settings, including in teaching and leadership roles.

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And the majority of men apprentices reported never having worked with a woman in their workplaces. Women and non binary participants reported feeling acutely aware that they were in the minority and described and reported feeling pressure to prove themselves as a result.

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I remember walking into TAFE Orientation Day and I locked eyes with one other girl and I was like thank God.

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Because I felt like I was getting stared down. I feel like the women that we've got employed, they do work that extra bit more.

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Because they're always trying to prove themselves. And they're brilliant and I feel like that too.

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I feel like you're on the back foot. You've got to show that you're as good as a man.

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And these descriptions are consistent with Holdsworth's findings that women employed in the construction industry report feeling as outsiders in their workplaces.

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And is consistent with bridges, findings that women in the construction industry here in Australia, in their context, it's in regional Australia that women as the minority are highly visible and as a result their work has the potential to become a gender issue.

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And finally, under the theme of gender norms and stereotypes, as you can imagine, there are a significant number of norms that were identified through the analysis.

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However, the primary stereotype related to gendered perceptions of ability and both men and women participants described this in both the construction industry and in the TAFE learning setting itself.

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And man apprentice reported. From an old trades point of view, what I've noticed is that older men just see women as pretty much incapable.

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They can't do that. They couldn't handle that. And women participants reported experiencing gender harassment relating to ability.

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The men that come in and they'll be like saying this openly in front of all the women in my workplace.

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Women are a liability. They are not as strong. They can't go as hard as men can.

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And this was consistent with Rawlings and Andersen's recent findings from their recently published paper around gender-based harassment relating to ability in other male dominated industries.

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There's this particularly in the context of professional sporting clubs and the inclusion of women as umpires in those settings.

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Where they observed that almost all participants had experienced where their work had been accompanied by blatant sexism through the questioning and degradation of their ability without any basis except for their appearance.

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And these negative perceptions of women's abilities is also consistent with the work of Koch and their findings around backlash from their study on gender stereotypes and employment decision bias that men may be sensitive to changes in the traditional gender hierarchy and as a result may disapprove of women working in

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male-dominated occupations.

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Overall, the research found a culture of hegemonic masculinity and tape construction apprenticeship training that's consistent with what's present in the broader culture of the construction industry.

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We found a culture in tape construction apprenticeship training that appears to be representative of broader social norms as found in the literature on male-dominated industries, a culture that stereotypes women and reinforces women's exclusion from traditionally male industries and that reproduces and reinforces rather than reduces barriers to women's entry

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and retention in the construction trade training. And finally, an industry based culture that is unsafe and harmful to all participants in the construction training arena of a TAFE college.

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And overall the research really provides further evidence to support Ray and Taretsky's assertion that there's a need for masculine industry norms to be reconstructed and redesigned for gender inclusivity in construction.

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And this research posits that exclusionary traditional ideas about industries, occupations and gender and associated oppressive hegemonic cultures can be transformed through critical dialogue.

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And so overall this research recommends the adoption of gender transformative pedagogies in construction workplace learning settings such as these tastes which is in line with the UNESCO gender transformative education recommendations and that's where we're moving into our next phase in this project to try all that and we look forward to reporting

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that. Thank you.

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Thank you. Thank you very much. So we are going to the next. Presentation which will be online So,

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So, you can share the screen now.

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I'm sure I'll just. Screen.

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Yeah, we can see it.

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Okay. Let's just say.

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Yeah, just full screen.

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Is this good now? Okay.

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Perfect. Yeah, it's perfect. Yeah, we can hear you. We can see it so you can start.

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Okay.

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Yeah, you can introduce a little bit yourself and Go ahead.

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Yes, yes, so, hello everyone. Greetings from India. It's a pleasure to be here virtually in front of everyone to present my work.

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I am working on a project that's titled The Impact of Kovat. 19 on government workers in India.

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Recovery with alternative models, fair trade, setting the agenda as I'm working on the garment industry and looking at it from the perspective of some of the voluntary standards that exist in this case specifically fair trade.

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So in India I'm a professor of sociology at the General Global Business School. It's a university in India.

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And at the same time, I'm also continuing to work on my PhD from Colorado State University in U.S.A.

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There there is a center for fair and alternative trade and I'm a researcher with them. So that's basically my profile.

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When we are looking at, the garment industry when we look at the global economy for that, we're seeing that there are structural imbalances in terms of how it is stratified.

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So what we are finding is that there is an internationally exploitative relationship that is built in in terms of how the economy is structured because we find that the major players or the retailers that place the orders are located in specific parts of the world more developed parts and the orders are being produced or the manufacturing or garment production is taking place

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in the lesser developed parts and the more developing countries which provide cheap labor, ready access to raw materials and just the production costs a lot cheaper and therefore economically it's a viable system because it owns higher profits.

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So that's the terrain that we're working with. But when we look at that, we understand that there is a major power in balance there.

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And the structure that we're working with in the global economy has a clear distinction between the powerful players, the ones who are the key decision maker or have the assets of the resources have the power and control of the system.

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They're located in one part of the world and the more vulnerable population that's suffering that is marginalized that does not do profiting as much as the others in the economy.

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They're located in a different part of the world. So global value chains of production therefore are built on these long established structures of gender inequality and COVID.

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19 is exasperated some of these inequalities between global north and global south highlighting the gendered aspects of these value chains.

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So now what is really important in terms of looking at it from a general lens is that manufacturing is associated with women workers.

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It's associated with poor political and economic conditions which seem to have worsened during the COVID-19 pandemic.

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Having staggering consequences for developing countries where almost 70% of working women are employed in the formal economy with very few protections.

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So already the economy was suffering. Women workers are primarily part of it. They are the ones who, help in the manufacturing of the garments that we see.

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And it is a vulnerable section already and the pandemic hitting had made the situation worse. There are 65 million workers who are women in this industry and there's a strong female presence and with the pandemic hitting in it has led to something it's called secession because of just how strongly women have been negatively impacted with

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it. When we look at the urban areas in India, the studies focus specifically on India. There are other regions as well which are impacted such as Bangladesh but focusing on India specifically we see that even in urban centers where you would have a higher participation rate for labor.

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There also we see that labor participation rates fell and they were much worse for women than men. So they were 9.3% compared to 67.4 for mail.

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While before COVID-19 women spent 6 more hours on average on unpaid childcare per week during Covid-nineteen women was spending 7.7 more hours than men approximately 31.5 per week which is like as good as another full time job.

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So what we're seeing is that it's not that women are not working in the pandemic or were not there.

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You know, visible for, the labor. They were working at home and domestic work increased, which anyways, you know, is a double work that women perform.

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Add to that some of the, social inequalities that exist because of the positioning of women in the stratification system in a country like India, especially in the northern region where patriarchy is very strong.

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Cast, class, gender, produce, you know, complications which are in one sense normalized in by women as well and it's very hard to see for some of them that this is violence exploitation.

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So there is a certain tolerance also because of the social conditioning which makes certain forms of violence acceptable or the fact that domestic labor is a natural extension of a woman's role in society.

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So women at times have been found to see supporting some of the structures that oppress them. And then in addition, you see work-related violence as well, which has been right before and after the pandemic as well with the insults, and sexual abuse perpetuated by a combination of pressure from above and part disparities on the shop flow that lead

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to a culture of bullying. Now that is the set of you're seeing society having certain social issues which then have a strong consequence on the economy and the economy also having its own set of issues in terms of how work gets done.

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So when we are looking at these 2, we have to see them in an intersecting way because they are connected, right?

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They are not so disconnected and what happens in the social site has consequences on the economy and vice versa.

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So when we're looking at an economic model then there are certain ethical concerns that are raised in terms of how we are profiting or how we are working with the system.

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This is especially been made blaringly clear after the pandemic, which helped put a spotlight on some of these issues because they were made much worse.

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The town being used secession or here we are talking about how they were immediate cancellation of orders.

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So orders were placed and around 40 billion US 1 billion dollars were cancelled after the pandemic struck. So people who are the most wonderful who were, you know, relying on daily wage were the ones who were axed out first when a crisis hit.

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So response to a crisis from Panicronic system is very important because you get to understand how it operates and those who have power, those who have resources and better.

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Resources to work with certain challenges such as a pandemic and the crisis that we experienced. You know, should have worked it out differently because they were well positioned to deal with it rather than those who are working daily for a wage.

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But it happened that way that the ones were at the, bottom and the most vulnerable were the first to get cut.

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So work orders were cancelled, which again created trouble for those at the bottom. Then, the kind of orders that they were, getting, those were again, 1015% below the pre-pandemic levels.

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So fair price, wage test was some of the issues that we saw which raised major concerns about human rights and how businesses operate especially when they are under threat.

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No of course when we look at the system you're saying well the government should also play a role but when the government mandates are there you know it's very hard to implement them because they economy is very complicated.

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Especially garment manufacturing. It's easier to control and you know kind of have that sort of monitoring of the big players in the garment industry but India runs on small and medium enterprises and within those also there are various factories, subdivisions and so on.

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So there's a lot of subcontracting that goes on. There's a lot of informal labor that happens.

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So it's very difficult to tap into that and try to assess what is happening. So it's been escaping that scrutiny and therefore the government has not been able to really put a heavy hands on some of these mad practices that have been going on.

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So there comes the role of voluntary certifications. Such as spare trade, which is trying to level the global inequalities that we see where the retailers or the ones you're giving the orders are in the more developed parts of the world, consumers are in the north and you have a manufacturing taking place in developing countries and where you

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have a very vulnerable population. So where we're looking at this, we're saying, well, there's need for everyone to pitch in.

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It has to be an ecosystem that needs to be generated. Just relying on the government will not help because you're talking about international economy.

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Just relying on the economic enterprises will not work because while they impact other groups as well. Society also has a part to play without conditioning the society or changing you know our socialization we cannot hope to achieve any changes in the economy.

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It has to be a joint project. So in that sense, we need different players. It has to be a multi stakeholder initiatives and Fair Trade does that because it requires regulation from all parties.

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It has a civil society component where in June NGOs connect with economic enterprises and they work with them.

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In a trade itself is an international NGO. So in addition to local civil society organization, we also have an international body overseeing the practices and the standards that they come up with have certain regulations have certain conditions that need to be met by the manufacturing unit so as to be insured that certification. So a fair trade mark is given.

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This would be there on the government which says a fair trade mark is given this would be there on the government which says that the production has taken place, which says that the production has taken place under certain conditions which communicate to the production has taken place under certain conditions which communicate to the consumer that they've been produced in fair and just conditions.

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So that's very important because it's a communication, it's transparency and it's also a visible indicator.

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Assuring consumers that what they are buying has been produced in sustainable and fair manner. In terms of consumption practices, we are seeing that there has been a shift, in consumption, which is helpful in bringing about these changes of fair production and manufacturing.

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We're seeing that, people are now increasingly conscious of that impact in terms of their choices with respect to clothing.

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So we don't need as many. So mass production, you know, took a hit where people started consuming less.

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They were rental services, then homegrown brands became more important because we understood what was happening in the international economy.

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On the flip side, however, because of the economic crunch, there was a tendency to, consume less and go for cheaper products to save on money, which again leads to the fast fashion problem or you know those cheap prices that garments have come at a cost because they're cheap because they've been have come at a cost because they're cheap because

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they've introduced under exploitative conditions under exploitative conditions. So it's not a fair price.

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So a lot of, quantitative conditions. So it's not a fair price. So a lot of, exploitative conditions. So it's not a fair price.

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So a lot of, conversation started picking up after, the pandemic hit. In addition to that, we are also seeing technological changes with digitalization, which is very important again, because that provides, a way to, get more transparency out there with respect to payments with respect to accounting for

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that. And ensuring that the informal labor is on the roll call of companies and they can be you know properly processed for the work that they are doing.

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While these voluntary initiatives are strong, are well supported by the government as well. Are supported by economic enterprises because they can connect the economic enterprises to their ethical consumer base.

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It's still very surprising that we have around 20 in India for textiles that are prominent but only to focus on labor.

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And labor is a pressing problem. It has been persisting and we know that women are exploited in the comment industry.

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Yet only 2 out of 20 are focused on the social component, one being fair to the other being gods.

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So, we have to look at that site as well. Why, some of these, challenges exist.

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With that, when do those that voluntary certifications that exist, there's very little form level analysis of what's happening.

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They exist, they claim, that, you know, these are the conditions, decent work, fair wages, health and safety should be guaranteed to the workers.

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What is happening on ground? There very little empirical data. So we need more research that brings all of those information from the field.

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And only then can we experience a revolutionary change in the way garments are produced, manufactured and consumed by people.

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Oh.

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You have only 1 min to finish, okay?

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Sure, got it. Thank you. So that's very important and therefore I'm focusing attention on the fair trade text as standard specifically where we're trying to challenge the business as usual approach bring in some of those ethical concerns at the same time activate the civil society with respect to conditioning and socializing people better

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to understand some of the challenges that come from various ways of stratifying people into groups such as class, caste, gender and so on.

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And also develop a network where people who are engaging in fair sustainable practices also get a consumer base that supports that way of conducting business.

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Sustainable practices also get a consumer base that supports that way of conducting business. So producers need to be, you know, connected to consumer so

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Yeah, I have to I have to you have to conclude now okay because we already exceeded 2 min.

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Yes, this is the last line. Yes, this is the last slide. So, in the university that I work for, we are looking at some of these research gaps.

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This is the memorandum of understanding that we have signed with fair trade and we are involving the youth which is again a very important stakeholder in our practices so that we can make businesses more sustainable.

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Thank you for overshooting on the time. That's all for me for now.

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Thank you.

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Yeah.

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Thank you, If you can stop sharing the screen. Yeah, thank you so much. So we are coming to the year next presentation.

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So let me share this screen again. So contrasting global gender gaps in STEM using Facebook data and offline indicators.

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Karolina, please the floor is yours. So you can say a few words about yourself and Thank you.

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Hello, everyone. Thank you for being here. So my name is Carolina and PhD student.

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And the Department of Digital and Computational Demography at Max Planck Institute for Demographic Research.

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And this is a piece of research that I'm conducting with Marisa Vas Conseil's from IBM Research, Brazil.

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So we are currently living in this what's called fourth industrial revolution. And we observed that during this period we observed a growing demand for workers in STEM.

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Science, technology, engineering and math. However, in these areas you all probably know. That the gender gap towards women, is still big and persistent.

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Here we have like a figure showing the proportion of male and female students in universities in the US.

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But as a personal example, I can tell you, I'm computer scientist. And when I started my studies I was one of the few women in the class.

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I guess around 40 students we were just 5 women just to give you a personal example of how the situation is.

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So I believe that in this context is important to understand, assess and mitigate gender gap. And here, what I would like to tell you is that Although most of these studies they use surveys to conduct this kind of assessment of gender gap across disciplines.

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And they are widely used and important. Some of the limitations such as the time and high cost needed to run a survey across countries.

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I would like to overcome by showing you this passively collected data from social media. Where we can measure these global gender gap.

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Across countries and disciplines related to stamp and non-stamp. And then I will present this large-scale analysis using Facebook data.

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And when I say Facebook, try to think about Meta, so Facebook, Instagram.

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I will answer these 2 research questions. First, how gender gap by college majors are distributed across the globe.

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Using Facebook data, keeping mind all the time that we are using data from social media. Keep in mind all the time that we are using data from social media.

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And maybe the population, it's not the population you were used to. Study and how these measures obtain from Facebook they are compared to offline gender gap reports.

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The methodology we created this pipeline where we collected a list of disciplines, stamp and non-Tem majors.

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Until we compute the gender balanced measures, gender balance measures for each country using Facebook data and I will explain step by step right now.

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We collected this list of 177 majors from a website called Handshake. And then we query these majors on Facebook as interests.

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So for those who are not familiar with this Facebook advertising platform, here's a screenshot of the platform.

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Of course I automatized a collection using an API. But if you have a Facebook account and you would like to play with this platform, that's what you will see.

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If you try to play with that. And basically this platform we can collect the expected amount of users on Facebook who match some demographic characteristics.

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For example, I can query the number of female users living in Germany. Interested in computer science and then I will see the range of people if I decide to launch an advertisement that would be the number of female Facebook users living in Germany interested in computer science who would see that.

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And the data, the data is totally free. So we call that for all the 177 interests or majors.

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For countries across the globe. We filter this interest because we would like to have interests that would actually have meaningful values Facebook has a threshold so every time your audience is lower than 1,000 for privacy reasons you cannot identify users so as a return it would give you a thousand which could be anything from 0 to 1,000 so we decided

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to keep only interest that had this meaningful values so at the end We managed to collect for 198 countries.

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142 interests that are split into 66 in interest that related to STEM majors and 76 not.

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And then we measure these gender balances. Before showing you these measures of gender balance, I just want to show you these overall gender balance on Facebook, which is pretty much the proportion of men using Facebook.

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This is not a surprising result or a new result. But I just would like to show you this map in terms of comparison when I show you the gender gap for stem and non stem majors.

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So here is pretty much the proportion of men using Facebook across 198 countries. So countries in blue, more men, orange or red more women using Facebook.

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And overall women are more Use more Facebook than men except Africa and some countries in Asia. Again, this is not new.

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What is new is that we decided to create a similar measure, the proportion of men interested in each one of these majors I told you before.

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Using, on Facebook. So this measure what's what is representing is the gender balance.

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So goes from 0 to 1. 0 means that females are dominating this audience. One, male or dominating, more men are interested in these majors than women on Facebook and 0 point 5 would be the perfect balance so we have like an equal number of men and women interested on that.

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And here I can show you for each country we calculated the median of these values. Remember that each country has a gender balance for each one of these major.

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So we would like to aggregate this number in in here the medium. And again, we see that women are dominating the interest.

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In these majors. But now we would like to split these majors into STEM and non-stem to compare them if actually women are always more interested in majors than men overall.

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And here is what we have for non-stand majors. So considering only non-stand majors you see that still women are dominating this metric here but the same is not true if we consider it stand majors.

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So if we select only a stem majors, we see that even though the population on Facebook is dominated by women is biased towards women once we sell stand majors we see that more men are interested in those measures than women.

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Just to give you an overall impression how the maps look like. So as I said before, women are more interested in non-standard majors than men.

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But men are more interested in state major than women. And just to show you. A few examples.

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So we selected the US, India, UK, Indonesia and Brazil to show the individual value of dismantled metric for each one of the majors in STEM or Non-stem.

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And even though we saw before that men are dominating this stem gender balance. What we see here when we actually split or we analyse individually these majors.

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Is that they are men are more interested in stand majors than women who But what is driven this result is engineering and technology.

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Because if we observe Technology and Engineering, they are dominated by men on Facebook. But life science and math, they are still biased towards women.

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So the second research question was OK, so how these measures using Facebook data are actually compared to offline gender gap reports.

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So here for the comparison I am got this data from the global gender gap index. Which is composed by different sub-indus sub indices that you can see here and the values they range from 0 which means this parity.

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2 one, which is gender parity. So just a reminder, they scales, they are a bit different.

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So I just put a reminder here for you because the global gender gap index growth goes from 0 to one, meaning parity.

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And our Facebook global. Gender balance goes from 0 to one but the perfect gender balance would be 0 point 5.

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And then when we compare these measures, what we saw is that our measure from Facebook and the global gender gap index they are negatively correlated.

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So what this negative correlation means is that countries with high gender gap or would be represented by this low global gender gap in index meaning a disparity.

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They have a higher proportion of men interested in these majors on Facebook. Which makes sense and we were quite happy to see this correlation.

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So to conclude. I showed you that the audience on Facebook is biased towards women.

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But when we when we select only in the interest in STEM majors, we saw that in 74% of the countries.

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Men dominate this audience. However, if we go even deeper on this stand majors, we see that what is actually driving this result is engineer are actually 2 measures in related 2 groups sorry related to engineering and technology.

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And. Finally, I showed you that our measure using Facebook data is highly correlated with offline measures of gender balance.

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Okay. I don't know what what happened here but That's it from my side and I hope that you enjoy this new way of measuring global gender gap using social media data.

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Thank you.

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Thank you, Carolina for very interesting presentation. So we are moving to the last presentation of this session.

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Which is online no blah you would like to hear from your side or you want me to share?

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Yes, yes, yes, please, make yes.

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I'll be sharing. Can I please have access? Thank you. Hold on.

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Alright.

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Yeah, we can see it.

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Yeah, alright. So good afternoon. It's a afternoon here. Good afternoon everyone.

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I'm Francis Michel Nuba. I'm from the Philippines. So today I will be presenting.

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My paper on barriers to economic and, economic participation, the case of a small island community in the Philippines.

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So here, presented here is the 2022 global gender gap report which plays the Philippines at the top nineteenth while the country has good standing in terms of health and survival and educational attainment.

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The country has underperformed when it comes to political empowerment and economic participation in opportunity. This also tells us that there seems to be a discomfort when it comes to education and economic participation.

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Looking at economic empowerment, which is the focus of this paper, we see that female labor participation rate is lower than males and there is also an income income gap where women about 2, $1,690 less than meals.

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Zooming in. On the countries statistics there are 8.7 million women in the country that are 4 and their separation versus when they are farmers, fishers or are residing in rural areas as these sectors are with high poverty incidences.

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Compared also to other sectors, only 10% of women work in the fisheries industry compared to 81% of males.

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Labor force participation rate of women in the fisheries industry is way below the national figure of 52% in the same period.

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In terms of income, women in the fishery sector earn about 10% less. Or $2.26 compared to the income of men which is 2.8 9.

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Dollars. In terms of laws, policies and programs for women, the country has the Magna Carta for women which is a comprehensive women's rights law that seeks to uphold rights of Filipino, especially among the marginalized sector.

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We also have the women in development and nation building act. We also have the Women in Development and Nation Building Act, which includes provision of at least 5% budget for gender and development programs.

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From 1995 to 2025 which mandates government administration to develop long term time bound framework plans for women empowerment and gender equality.

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This plan is a translation of the Beijing platform for action. And projects and programs for Filipino women.

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The in terms of the fisheries and agricultural sector there is the agriculture and fisheries modernization plan which focuses on 5 concerns for security, poverty, alleviation, social equity, income enhancement and profitability.

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Specifically for farmers and Fishermen. Global Competitiveness and sustainability. My interest is, so why despite all these legal frameworks and a good performance in terms of education.

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Why is it that Filipino women participate? They still find it difficult to participate in the economy.

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And sociologist have continuously passed out the relationship of 3 of these 3 structured culture and agency and in these paper I followed Archer in which I looked at structure agency and culture separately.

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So the objectives of my study are to identify which structural and cultural factors affect me men's participation in the small island community of my study and to explore later the interplay of these factors and how it contributes.

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Or hinders women's economic participation.

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While the effects of structural barriers are quite easy to comprehend, I am also interested to understand how Zendar beliefs and ideologies in its fluidity guide gender role and constraint agency.

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So based on the literature, these are the inhibiting and inabling, factors. Scholars at attribute the difficulty in attaining success in the economic empowerment Arena to the strong division of labor where women are the ones primarily responsible for household and care work.

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And the amount of time women do these chores. There are also structural barriers in education, access to resources, access to markets, norms and attitudes and entrepreneurship and innovation.

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Meanwhile studies show that egalitarian gender relations, access to resources and livelihood diversification are enable factors for women's economic participation.

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So this is study used phenomenological study which focuses on the descriptions of what people experience and how they experience it.

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The data was collected using life story with 25 women in the community where we released back their earliest experience with regards to the work they do up to that day of up to the time of the interview, period of the interview, key informant interviews were also conducted to understand how government agencies contextualize or understand the the situation of the home UN

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meeting.

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So the study site is a small island. One of the 22 Barangais of a municipality south of Manila.

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It is approximately 85 kilometers away from the city center. The community is subdivided into 2 areas.

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And there is only one element in school. In the area there is no electricity they have a big mobile signal and the major source of likelihood in development is fishing, although there are some other agricultural activities such as vegetable farming, and then in once in a while, women engage in service.

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Such as laundry, but very few because most of the people both of the women there are not working so they have time to do their chores and not everyone can afford also to pay for a household work.

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So the fact doors found to hinder economic participation are as follows. There's the gender ideology enroll.

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Limited livelihood opportunities and the remoteness and lack of features organization in the community. As regards to gender ideology and role, women's primary, because women's primary role is caregiving and they believe that they are Their work is to be a secondary breadwinner through the household income.

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Women are less likely to work outside the community once they get married. Interviews show that when husbands got sick, though women would work to the point that they would leave the community to find a job which was an acceptable setup for single women because these women when they were still single Almost all of those that I have interviewed,

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went to other places to work. Basically to help support the family of their orientation. And also because, there is limited livelihood.

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Opportunities in the community. This women, this single women would have to engage in labor migration to find working urban spaces.

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Other push factors aside from, temporary illness of the husband is husband's death the separation with husband or extreme events such as typhoon which has been or extreme events such as typhoon, or extreme events such as typhoon, which, hinders we meant to go fishing.

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That's when it has been or extreme events such as typhoon, which, hinders we meant to go fishing.

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That's when women decides to go they have they and they can go to work but This highlights that the work that engaging in economic work is secondary for them.

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Let me also mention the importance of a strong network. Which is vital to allow women to work because when they get married and when they have young children they cannot their primary reason for staying in the community.

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Is taking care of their children. So, when team members are available and are willing to take on care giving roles, that's when, women will be more willing to decide to engage in economic in work outside the community.

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And also because most of the participants only finish primary education because there is no secondary institution in the community.

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Some of the work that I that are available to them is to be household workers and in some cases employers would not allow them to bring their children to where they work.

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So that's also another hearing for them. But there are though there are also those who finish second diet education where they can work as factory workers or store attendance when they were still single.

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So, in terms of finding work, social network is also instrumental because the community is far from the centre.

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They cannot afford to spend money and allow one staying in the city center to look forward. So they want to be they want to assure that they have work ready, readily available to them when they leave the home unity.

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So women's migration when they were still single somehow shows the lack of livelihood.

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In some communities women fishers are can be observed but in the community of Buddha wine and women are not engaged in fishing but they do engage in selling fish or

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They would. Facilitate capitals and higher features, but these are the women who were able to continue the fishing industry that were left by their either their husband or their father.

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In the interpreter neural activity that is available in the community. They are able to put up small stores.

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However, they also mentioned that this, small businesses do not really drive because the community is generally upward.

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Finally, because of Siruma's characteristic as a small island, it is separated from major trade and the lack of diversified livelihood opportunities as well as their their dependence on natural resources.

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Makes fishing activity and earning more challenging. More over for organizations that are in charge of providing opportunities for this community they believe they would mention that it's difficult to visit the community because of the distance.

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They that transportation is challenging for them. And the lack of functional people's organization also prevents the officials to be invited in government programs.

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So I summarize the factors in this framework where structural factors include the presence of young children, education and painting limited capital resources and limited network to be hindering agency and women's economic participation while cultural factors such as ideology and gender also affects their decision to go atto-engage in work.

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Thank you so much. It was perfect timing. So can I please invite the speakers for today to sit here so to take questions up front.

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And the presenters. Online also switch on the camera. So please stop sharing the screen.

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Yeah, Michelle, can you stop sharing your screen?

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I can't seem to find where to stop share. I, sorry I can't find the where.

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Okay, perfect. Yeah.

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How do I stop sharing? Oh yeah, I found it there. Thank you.

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Okay, perfect. So we have, here and we have Michelle. Right? So,

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Now we are ready to take the questions from the audience. But you need to speak to the microphone so that, online guests and participants will hear us.

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I think it's a fascinating session because we had the opportunity to look and to the gender inequalities in different countries in the labor market.

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So we have Canada, we have Australia, we have India we have Philippines as a country cases and we have 2 brilliant talks across national perspective.

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Was labor low indicators and Facebook opportunity data collection so any questions for all the speakers. Most welcome.

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Yes, please.

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Thank you. I've got 2 questions. I just wanted to say thank you to all the panelists.

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Excellent presentations. The first question is to first presentation. Around comparing

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The legal. Agenda. Very countries is in Iran and I wondered whether Any of your work was comparing particular countries.

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Each other it struck me looking at your maps that particular loans in North America, the United States. Canada particularly with the United States comparing to the Soviet Union in relation to things like

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I believe and so both.

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Was quite significantly different. And that was surprising to me. I wondered whether you want

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That's my first question. I have a second question for Yes, yes. Let's, let's collect those questions so that way we can give the floor to all the speakers to answer.

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My second question is to the third presenter and I wondered I thought the The presentation was terrific and You mentioned the same of perceptions Chinda.

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And I was interested in that. And in particular, whether you thought there was a difference in the data in relation So what main participants sitting in relation to perceptions of gender.

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To your women participants, particularly in relation to the age differences. Quite steadily about that that you could

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So I would suggest we can collect some more questions, right? So and then we will have a flow of answers.

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Any other questions to participants? To their speakers?

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So meanwhile I have also a few questions. So first of all, to the first speaker, yes, about paternity leave and father's leave.

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So you showed us beautiful nap. About the countries and where the percentage of I mean like how well are doing the countries in terms of allowing fathers to take number of weeks.

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So however in some countries even the law is there but the cultural norm is not there. So What is your idea?

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I mean, like, maybe there should be additional map on like actual behavior of fathers. For example, in Russia it was green.

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I'm coming from Russia originally, but I do know that there are like 0 men who would take any paternity leave in the country because even if you ask it's like we were saying something like impossible I mean like something like very very Yeah, interesting to do.

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So, I also have a question about He India so I know that Sneeha, you can hear me?

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Yes. So I know that it's a very interesting dynamics of labor force participation among women. Which is from 60 seventies it was about 40 50% of labor force population.

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I mean like the females female labor force participation rate was about 40 50 but During the last 30 years it didn't raise up more than 2022 25% So do you have any like explanation of why it's like that because the country is moving towards globalization so I mean like more economic perspective so what's

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what's going on behind this low, extremely low participation rate for females in the labor market, especially if you compare this is economic situation of country that time and now.

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And I have also a question about limitations of the studies on Facebook. So. What what can you say about the limitation for first of all which year of the study you took the data for Facebook is at like 202-12-2230r like previous and it was before COVID after Covid and how did you overcome the difficulty that people

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might not put any interest. I mean like what was exactly the question or information about interest and major so In my profile, for example, I don't know if I have like my occupation or something like that

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Yeah, so and I have also a question to the last speaker Michelle right so about migration and, And, Gender representation in outgoing migration.

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So Philippines actually one of the country which is. Supplying a lot of migrant workers across the globe.

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And it's the only one country which is like the government regulates the wages that the Philippines, the Philippines receive abroad.

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So it's carefully monitoring their rights and safety of the Philippines who are going abroad and they they work a lot on remittances right so And I know that it's one of the countries where.

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The share of women in number of employees workers going outside the country is very high. So how does it affect the the gender structure of the local labor market and also education.

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So it's one of the top educated migrants across the globe because as soon as they decide to go abroad I think there is some programs that the government teaches them like English skills and other skills where you can actually learn, right?

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It's one of the unique experiences across the world. So what can you say about that?

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Any other questions? Yes, please. We have question online, yes.

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There was some hand.

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Okay. This is a question for Brett Woods and team. Hi, I'm Donna Bridges from Charles, Sturt University.

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And I have researched and reading in the area of vocational education. And women and trade specifically around sexual harassment.

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I wonder if you also in encountered stories about social harassment, more personalized than the stories. I heard about their deep pick.

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Okay, so this is a question to you. So any more questions? Okay, we can have a second round.

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So let's give the floor to the participants to answer please. Great. So to answer the question about.

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Different comparative groups. So we have done comparisons that are regional. Sometimes we do it when we want to dive deeper into a question and it's too hard to get data across 193 countries to do it.

466
01:32:35.000 --> 01:32:49.000
So we've done studies across the OECD when we're trying to understand. A portability of benefits or questions about who's eligible for benefits and data on average wages.

467
01:32:49.000 --> 01:32:57.000
Because of that's been too difficult to obtain. We've also done deep dive studies on sort of national differences.

468
01:32:57.000 --> 01:33:08.000
We just launched a data set on paid leave in US states that goes really deep into the eligibility. We've done similar studies in Canada and India and China.

469
01:33:08.000 --> 01:33:25.000
But the global data and of itself, our experiences. Is it is really powerful when we started building our data on page parental leave it was the US serving on the soap in Papua New Guinea in some small Pacific island states.

470
01:33:25.000 --> 01:33:30.000
We thought the data would move the US. Certainly policymakers have been. We thought the data would move the US.

471
01:33:30.000 --> 01:33:41.000
Certainly policymakers have been receptive to it. We thought the data would move the US. Certainly policymakers have been receptive to it.

472
01:33:41.000 --> 01:33:52.000
Global data does really have the power to, I think, dispel the myth that countries can't afford to do better on these policies and that change isn't feasible.

473
01:33:52.000 --> 01:34:04.000
To the question about paternity leave. I think that's a really great question. I took out a slide from this presentation due to time that I think would have answered that.

474
01:34:04.000 --> 01:34:19.000
For men to take leave, a big part of it is how it's structured. That research evidence is really strong that paid leave needs to be reserved for men or their needs to be incentives for them to take it.

475
01:34:19.000 --> 01:34:25.000
Going to leave. Men almost never take it. That's the case of how it's structured in Russia and many other countries.

476
01:34:25.000 --> 01:34:35.000
So that type of policy design decision matters as well as affordability of leave. I think you mentioned Canada's policies.

477
01:34:35.000 --> 01:34:37.000
Canada's 55% wage replacement rate. That's an issue of take-up and gender equality that matters for people.

478
01:34:37.000 --> 01:34:51.000
We have also done really rigorous studies matching this on to household survey data to look at what happens when you change the laws.

479
01:34:51.000 --> 01:34:57.000
And the answer is it also changes norms so it changes norms around who should hold jobs when jobs are scarce, we look at that using world value surveys.

480
01:34:57.000 --> 01:35:12.000
So Yes, we need to work on norms, but changing these laws can also help to shift some of those norms.

481
01:35:12.000 --> 01:35:18.000
So.

482
01:35:18.000 --> 01:35:23.000
Tim, I'll come to your question first and

483
01:35:23.000 --> 01:35:35.000
Seemed identified that one of the themes that we found across the border culture that I didn't dig into and partially that's because I'm not sure I have landed it yet or know how to make sense of this.

484
01:35:35.000 --> 01:35:47.000
One of the things that came out of our analysis was his perception. That this is a that gender inequality and everything that's sitting around that is a generational issue.

485
01:35:47.000 --> 01:35:57.000
And I use the word perception because this is is something that was repeated to us a number of times by basically all participants.

486
01:35:57.000 --> 01:36:10.000
Men apprentices described this in terms of the perceptions from their bosses on sites and then from teachers around, women, teachers and apprentices, voice the same things.

487
01:36:10.000 --> 01:36:26.000
And this was really interesting to us because I think early on we wanted to dismiss this really as sort of Something that's quite aist or perhaps a bit of a cop out that we're not actually examining and exploring structural elements here in the ways.

488
01:36:26.000 --> 01:36:37.000
That power and this masculine culture. Please out for me the real concern and the issue I want to dig into more is that because there's an assumption that was or a perception that was verbalized.

489
01:36:37.000 --> 01:36:50.000
Over and over there. Essentially, I'm probably quoting actually from a participant. Really the goal is we just have to wait these people out and when this older generation dies it's gonna be much better.

490
01:36:50.000 --> 01:37:03.000
It's almost word for word in some ways. For me that's deeply problematic because that limits our capacity for capacity of participants hope or our capacity to do any kind of structural change to really a waiting game until people leave.

491
01:37:03.000 --> 01:37:22.000
But also it doesn't allow us to unpack perhaps some of the false consciousness that's there that we assume that younger people are coming through ignoring the fact that they're being socialized into these settings with these older kind of gatekeepers and just assuming they get this and there'll be nothing else that's going

492
01:37:22.000 --> 01:37:29.000
on. So that's a theme we're still playing with. I would value Thoughts around how we We can continue to explore this.

493
01:37:29.000 --> 01:37:40.000
It was a theme that continued to come through, I think, in the analysis. Despite wanting to sort of push it away a little bit but not certainly we've landed.

494
01:37:40.000 --> 01:37:51.000
Thank you for the question. And to Donna at Online and I can see that Elizabeth is online too, so hello.

495
01:37:51.000 --> 01:37:58.000
We, it would be a delight to. Find time for our teams to sort of sit down and explore.

496
01:37:58.000 --> 01:38:07.000
Our research areas of course we've read some of your findings from your regional work and it would be interesting to think about.

497
01:38:07.000 --> 01:38:14.000
How that similar and dissimilar from particularly our focus in the learning setting and how that relates to your research.

498
01:38:14.000 --> 01:38:25.000
In terms of the question specifically around sexual harassment, yes. They were absolutely disclosures of people's experiences.

499
01:38:25.000 --> 01:38:41.000
I think the the orientation of our of this researchers was action research and this was very much to inform interventions based on for area and pedagogy thinking about ways that we can come in and help.

500
01:38:41.000 --> 01:38:48.000
Transform those cultures. So the research and the ways that we guided the questions were much more around

501
01:38:48.000 --> 01:39:02.000
Thinking about other experiences that are perhaps unseen and and so so we obviously captured these things but that wasn't a cool focus I think that would be great to touch base with your teams.

502
01:39:02.000 --> 01:39:15.000
Thank you for the question. Yeah, thank you. I would ask this speakers to answer a little bit to the point so that we have only 7 min so that everybody can get a chance to answer the questions.

503
01:39:15.000 --> 01:39:20.000
Should I answer an hour? Wait for your one question. Yeah, please go ahead and unavailable.

504
01:39:20.000 --> 01:39:27.000
Okay, yeah, I will be quick. First, about the year of my data is 2,021.

505
01:39:27.000 --> 01:39:43.000
And limitations. I will start by the point you raised about the interest that for example not everybody actually add where they work or where they study for which field.

506
01:39:43.000 --> 01:39:58.000
But then we have something that it's good and bad at the same time about Facebook. Is that this data it's not only what you report as your major or work field.

507
01:39:58.000 --> 01:40:13.000
Facebook also infer part of, your interests. So it's the same for food you like, celebrities, people, lifestyle, sports, everything.

508
01:40:13.000 --> 01:40:31.000
So partially is what the user express on Facebook and self report. The other part is in for it by Facebook depending on what you search, what you like, what you follow.

509
01:40:31.000 --> 01:40:46.000
And so on. So this is, at the same time one limitation because it's what called a black box algorithm so we don't know exactly how they are inferring that and they will never tell us.

510
01:40:46.000 --> 01:40:59.000
But, at the same time. It's something we are measuring something broader than just what you work or study.

511
01:40:59.000 --> 01:41:04.000
Okay, so, sneaker please, if you can answer your question.

512
01:41:04.000 --> 01:41:10.000
Yes, thank you so much for giving that question to me. It was about women's dropping labor force participation.

513
01:41:10.000 --> 01:41:13.000
So when I think about it, what's critical is to see the seasonal nature of the comment industry.

514
01:41:13.000 --> 01:41:19.000
So when the season is on, there's greater demand when the season is off. You know, the demand dwindles.

515
01:41:19.000 --> 01:41:28.000
And so we see a lot of fluctuations in terms of the need for labor. That is one factor that impacts it.

516
01:41:28.000 --> 01:41:44.000
And when the demand is high, generally what is done is there's a strong reliance on the informal economy or home-based workers, women who don't come to the factory but they work from their homes and they have the skills necessary to do the employee or to do stitching and so on.

517
01:41:44.000 --> 01:41:52.000
So a lot of work gets passed on to home workers. This is critical because this gets under reported, right?

518
01:41:52.000 --> 01:42:02.000
It's not even reported in many cases. Because of the fact that those who are on the company factory payroll, they are the ones that have to, you know, in principle in theory be given all the benefits.

519
01:42:02.000 --> 01:42:09.000
The pay, the wages that have to guarantee a decent living wage. So, that is one problem.

520
01:42:09.000 --> 01:42:20.000
That not much of it is under reported. It's also very volatile because of the seasonal nature of the way the industry functions.

521
01:42:20.000 --> 01:42:32.000
And then to understand the issue with home-based workers as well because they're out of the network out of the circuit formally, but they do contribute in a nature way in terms of getting the orders in and running the businesses.

522
01:42:32.000 --> 01:42:43.000
And of course because they're exploited there is again source of income and profit. At the same time when we're looking at the skills of women, mostly women are employed with, you know, skills that are not very advanced.

523
01:42:43.000 --> 01:42:59.000
So they don't reach the higher levels or they don't reach leadership positions. So as we move up where we see power in, we see again dropping enrollment of loving participation of women in this particular sector.

524
01:42:59.000 --> 01:43:02.000
Thank you.

525
01:43:02.000 --> 01:43:14.000
Okay, while Michelle is preparing for answer, I have also one question about the Canada. So since you did this research in highly educated positions, right, and occupations.

526
01:43:14.000 --> 01:43:28.000
So maybe you'll have information what is general pay gap in Canada and maybe you have information where this gap in which occupations is highest.

527
01:43:28.000 --> 01:43:34.000
And where it's lowest but first we will give the floor to Michelle to answer the question of her and then we come back to you okay Please Michelle.

528
01:43:34.000 --> 01:43:45.000
Thank you. Thank you. So for this study that I did, I only looked at internal migration, but you're right that we have a high external labor migration in the country.

529
01:43:45.000 --> 01:44:02.000
Which is the same also for the for the community which I studied when women leave the household their other female members would take on their the child reading rules that they used to that they used to do.

530
01:44:02.000 --> 01:44:12.000
So it's usually aunties or grandparents that they used to do. So it's usually aunties or grandparents or sisters who would take on that work.

531
01:44:12.000 --> 01:44:24.000
And also, in the Philippines, we can hire household helpers, but, in contrast, no, in contrast with the external labor migration and the internal labor migration.

532
01:44:24.000 --> 01:44:30.000
There is, yeah, there is an expected more economic benefit in terms of external labor migration than internal labour migration.

533
01:44:30.000 --> 01:44:47.000
So internally more migration, based on the study that I did is a bit, a lower rate when it comes when once they got married.

534
01:44:47.000 --> 01:44:54.000
Unfortunately, I did not look at in turn, Thank you.

535
01:44:54.000 --> 01:45:05.000
Thank you. So. Excuse me. The gender wage gap in high income countries is actually astonishingly stable.

536
01:45:05.000 --> 01:45:17.000
I can't tell for every country and for every occupation the OECD average posted at women earning 77 cents for every dollar earned by men in the general labor force.

537
01:45:17.000 --> 01:45:31.000
Canada, moisture at all, evaluated. 77 cents for every dollar that men earned in the general labor force and we did another study where we looked at university educated stem health and education professionals in the prime working years. Guess what?

538
01:45:31.000 --> 01:45:47.000
It was about 77 cents earned by women for every dollar earned by men. One of my graduate students just looked at the Canadian psychology professional.

539
01:45:47.000 --> 01:45:58.000
Workforce again highly educated. Oh my god, it was I swear it was 77 cents for every dollar earned by men for the unadjusted figure.

540
01:45:58.000 --> 01:46:07.000
I don't know offhand what is the occupation that has the highest wage gap, but the higher the average salary, there's just more room for men to earn more.

541
01:46:07.000 --> 01:46:15.000
So if you're looking at it just as a percentage that kind of skews things a bit because hierarchy, higher paid occupations have more room for men to earn more.

542
01:46:15.000 --> 01:46:22.000
So the percentage difference tends to be wider.

543
01:46:22.000 --> 01:46:33.000
The main office. Yeah, I appreciate the session. Thank you very much for all participants. I would like to ask, to make a picture if you don't mind to make a group photo.

544
01:46:33.000 --> 01:46:34.000
So if our speakers online can also switch on the camera. And join us for the fourth quarter will be good.