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Record W4367604959 · doi:10.1002/fee.2631

Allyship requires action

2023· review· en· W4367604959 on OpenAlexaff
Ezra J. Kottler, Kyle M. Shanebeck, Sharon K. Collinge

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2023
Typereview
Languageen
FieldDecision Sciences
TopicInterdisciplinary Research and Collaboration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTransgenderQueerHarmPovertyMental healthFace (sociological concept)Affirmative actionLesbianAction (physics)Public relationsPolitical scienceCriminologyEmployment discriminationPsychologySociologySocial psychologyGender studiesLawPsychiatry

Abstract

fetched live from OpenAlex

Queer and especially transgender ecologists face unique barriers in the pursuit of professional training, resources, and career opportunities, and without targeted actions to overcome these barriers, motivations to make our institutions more equitable will not translate into meaningful change. Saying our institutions are safe for and welcoming of LGBTQ+ people is insufficient to achieve the necessary outcomes. Though social progress has made it possible for many LGBTQ+ scientists to live openly without fear of job termination and workplace violence, reports indicate that queer people remain 17–21% underrepresented in STEM fields and are more likely to be professionally devalued, harassed, and career limited than their cisgender/heterosexual colleagues (Sci Adv 2022; doi.org/10.1126/sciadv.abe0933). Simply put, if we want to create equal opportunity for LGBTQ+ scientists, allyship requires action. Many LGBTQ+ scientists feel the need to hide their identity and self-police their behavior to avoid discrimination, which takes a toll on mental well-being. Isolation, mental health challenges, and poverty also harm career goals, limiting opportunities for training and advancement. Poverty disproportionately affects LGBTQ+ people, who are more likely to be homeless, are less likely to own their homes, and have no federal protection from housing and rent discrimination in the US (Williams Institute 2020; https://escholarship.org/uc/item/3cb5b8zj). There is no federal law preventing discrimination in insurance coverage and healthcare, and there is a shortage of physicians with sufficient training to treat transgender patients (South Med J 2021; doi.org/10.14423/SMJ.0000000000001261). One of the authors of this editorial found their postdoctoral job prospects limited by this shortage, as they had to pass on applying for ecology positions that were too remote from any trans-informed medical practitioners. Field research and travel can be especially difficult for queer scientists. When a person goes through a body scanner at the airport, security presses one of two buttons (male, female), and transgender people can face invasive pat-downs and harassment when their bodies do not match the assigned scan. At their research destination, queer ecologists may then be at risk from anti-LGBTQ+ laws or threats to their physical safety depending on the country, region, or state in which they conduct their work. We need concrete actions to address these barriers to daily life and work for queer ecologists, or we will continue to lose bright and enthusiastic scientists at early career stages. To support LGBTQ+ ecologists, we need to implement change across all scales of our work environments. At the broadest scale, funds should be set aside to address the barriers that LGBTQ+ ecologists face, including opportunities for grants and scholarships. For relocation, housing, and travel, institutions could provide funds in advance, as opposed to reimbursement: an unnecessary financial strain on minoritized graduate students. We need adequate access to healthcare, with coverage to seek LGBTQ+-informed healthcare. We also need data collection on LGBTQ+ scientists from institutions so that underrepresentation can be better studied and remedied. The US National Science Foundation's decision to ignore gender and sexual diversity in their workforce surveys’ demographic questions sets a concerning precedent (Open Letter 2023; https://bit.ly/3Zqpbi6). In workplace settings, normalizing (but not requiring) pronouns during group introductions is one basic action that can be adopted. Additionally, workplaces should require participation in in-person harassment and sensitivity training on a regular basis. There should also be systems in place for accountability and reporting of discriminatory incidents with external nonpartisan mediation as an option for complaints. At the interpersonal level, we advocate for support for your queer mentees and colleagues when they disclose an obstacle they’ve encountered, even and especially when their experience does not align with your own. You don’t have to understand our experience to respect and believe us. Prioritize the safety of researchers over data and other research projects. This applies to all safety concerns in field ecology but is particularly critical regarding identity-related safety issues. If you are a principal investigator of a lab that works in regions where it is illegal or unsafe to be LGBTQ+, it is your job to provide your queer students with good alternatives for equivalent fieldwork experience. Allyship is a continuous process made up of discrete actions and takes commitment to equity, compassion, and other core values. As academic ecologists, there are many demands on our time that are unpaid or contribute minimally to our advancement in highly competitive fields of work. For this reason, we must encourage institutions to better incorporate DEI work into evaluations of tenure and grant deliverables so that people continue to improve DEI because it is part of their job, it helps us do better science, and it is the right thing to do.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score0.805

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.191
GPT teacher head0.444
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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