Today much of the world is reeling in shock at the extreme hate crime attack in a queer club in Orlando, that left 50 dead and over 50 injured. This is the brutal, violent edge of the spectrum of marginalisation and discrimination we try and undermine through equity work. I have no words, just deep deep sadness, and deep deep anger. And thoughts of solidarity and strength for my LGBTQ colleagues, students, friends, and wider communities around the world. Kia kaha!
Apparently, academia has high (“disproportionately high“) numbers of “gay and lesbian” staff. That’s fantastic – it suggests that the university provides a workplace environment that is a welcoming for LGBTIQ (lesbian, gay, bi, trans, intersex, queer/questioning) academics? But does it, and if so, what does that look like? The Times Higher just published a piece asking How Welcoming is Academia to LGBT Staff? in the UK. The answers suggest that overall, higher education does provide a fairly inclusive workplace environment, where being out is possible. But this doesn’t make being queer* & out academic always easy, and stories from academics reveal the potential complexities. In 2009, my colleague Victoria Clarke and I edited a dual Special Feature in the journal Feminism & Psychology and Special Issue of the journal Lesbian and Gay Psychology Review. We asked questions about whether the personal is pedagogical – around genders and sexualities in the classroom – and explored how LBGTIQ academics negotiated heteronormativity in and through their practices. Like the piece in the THES, we focused on academics’ voices. We asked them to reflect on their experiences, choices, and practices, in the context also of pedagogical theory around visibility and critical engagement. Both our project and the THES piece show that at the same time as universities typically offer fairly ‘safe’ environments, this cannot always be taken for granted: experiences vary, and the intersection of things like the localised university context, the person’s various identities and perspectives, and the broder sociopolitical cultural context, all come into play.
Despite some fairly rapid gains towards equal rights and opportunities for LG (less so trans) people in many Anglo/western countries, ongoing challenges to full- and free- participation are recognised in equity work around LGBTIQ populations. At the UoA, LGBTI staff and students are equity groups; our Rainbow Science Network is part of a university-wide LGBTI network that combines student and staff perspectives. Staff and students often intersect most regularly in the classroom, and inclusivity becomes evidenced not only through what we teach (and what we don’t teach), but how, as teachers, normative and non-normative identities come into play.
Victoria and I also researched experiences of queer students on campus (both UK and New Zealand; sadly not yet published, in full, but discussed here). That highlighted some of the very persistent and sometimes pervasive ways heteronormativity shaped students’ experiences. One of my students explored NZ data, and found students reported that the university offered both a place of inclusivity (“I can be myself”) and of marginalisation (that this came with “with a side of homophobia-flavoured rice”). Sheffield Hallam University recently published a much fuller report into the experiences of undergraduate students, focusing on the entirety of the university UG time (including selection choices). It likewise highlights that issues of marginalisation and discrimination remain challenges for LGBT students, including within the classroom – and found connections between (negative) experiences and student retention. Back closer to home, a 2012 Unitec MHS thesis examined LGBTIQ students’ views around campus climate, and compared them with straight student responses. What that nicely illustrated was the way straight students could perceive an environment as somewhere where ‘it’s fine to be gay’ and all identities are equally possible and accepted, but that view or experience was not shared by LGBTQI students.
*I use queer here to refer to sexual or gender identities outside the heteronorms and gender-binary, recognising that lots of people don’t choose that label.
Yesterday, I went to a seminar at AUT on Testing theories of gender discrimination using linked employer-employee data, presented by Economist Isabelle Sin, based at Victoria University. The analysis explored the question of what proportion of salary difference can be attributed do a gendered bias. But it tackled the question in a way I hadn’t seen before. By exploring higher-level income data – based on PAYE information from IRD – and industry/employee data, Sin and co-authors aimed to calculate ‘productivity’ based on gender, and salary based on gender, and compare the two. Not being a quantitative analyst, some of the detailed analytic tables were hard to follow , but the gist of the analysis is that across a very large sample of private-sector, for-profit companies, women’s productivity can be calculated as 86% compared to a 100% for men, but salary is 74% compared to 100% for men (taking part-time/full-time status and certain other factors into account). This average discrepancy – effectively a 12% gender-pay-gap – varied also by age categories, and a finer grained analysis revealed the gap differs considerably by industry category.
What wasn’t defined clearly was what productivity is – this may be a well-defined concept that holds up well in economic analysis, but I struggle with the concept, in lots of ways. I don’t like way it evokes a very linear and literal conceptual model of workforce contribution. Furthermore, as noted in the questions, the lack of a gendered-analysis of industries themselves meant that those which came up as most/least disriminatory didn’t necessarily map ‘common-sense’: for instance, libraries, which tend to have a female-dominated workforce, was included in the industry-band which appeared most-discriminatory (though this may in part reflect issues of gender-distribution across that workforce). Farming in many forms was the least discriminatory, which may at least partly reflect the pay-data used… It was based on PAYE data, meaning contractors were excluded.
Overall, the analysis was interesting – it provided a very similar number to other estimates of the gender-based pay gap. But it also highlighted the value for detailed or micro-focused, and specifically gendered, analyses. Furthermore, as other research indicates that race/ethnicity also impacts salary, including here in NZ, I believe that needs to always be kept present in analysis of gender-based pay gaps.