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Record W2571983349 · doi:10.1080/15313204.2016.1263817

A Mixed-Methods Inquiry Into Trans* Environmental Microaggressions on College Campuses: Experiences and Outcomes

2017· article· en· W2571983349 on OpenAlexaff
Michael R. Woodford, Jessica Joslin, Erich N. Pitcher, Kristen A. Renn

Bibliographic record

VenueJournal of Ethnic & Cultural Diversity in Social Work · 2017
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsWilfrid Laurier University
FundersCollege of Education, Michigan State UniversityNational Center for Institutional Diversity, University of Michigan
KeywordsPsychologyInclusion (mineral)Mental healthClinical psychologySocial psychologyDevelopmental psychologyPsychotherapist

Abstract

fetched live from OpenAlex

The experiences, including with environmental microaggressions, and well-being of trans* collegians remain an under-researched topic. In this mixed-methods study of a survey sample of 152 trans* collegians, multivariable regression findings suggest that the frequency of experiencing select trans* environmental microaggressions (e.g., not having access to comfortable bathrooms as a trans* person) are associated with increased risk for poorer academic outcomes (e.g., developmental challenges) but are not associated with mental health outcomes. Furthermore, interviews with 18 trans* collegians suggest that students face several systemic microaggressions, including difficulties advancing trans* inclusion. Various reactions, including paths of resistance, were identified. Implications are discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.144
GPT teacher head0.469
Teacher spread0.324 · 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.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations68
Published2017
Admission routes1
Has abstractyes

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