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Record W4395694134 · doi:10.1080/03075079.2024.2341971

The case of tenure and promotion: an examination of Title VII and minoritized faculty representation

2024· article· en· W4395694134 on OpenAlexaff
Michelle Lau, Renee Flasher, Lydia Didia

Bibliographic record

VenueStudies in Higher Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsBrock University
Fundersnot available
KeywordsHigher educationPromotion (chess)Representation (politics)PedagogyMathematics educationSociologyPolitical sciencePsychologyMedical educationPublic relationsMedicineLaw

Abstract

fetched live from OpenAlex

This quantitative study examines all discrimination lawsuits filed against institutions of higher education by faculty in the United States involving tenure and promotion throughout 1977–2022. Using institutional faculty gender and race data, we examine the association between Title VII tenure and promotion lawsuits and representation of minoritized faculty in academia. We find an association between institutions involved with a discrimination lawsuit and greater disparities for women and intersectional minoritized faculty. The results underscore that while gender remains an important variable for understanding the minoritized experiences of faculty in higher education, the perception of fairness is further skewed for individuals with an intersection of gender and race to their person. This study contributes to research examining tenure and promotion denial lawsuits to better understand the barriers of career progression for minoritized faculty in academia.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.005
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.331
GPT teacher head0.471
Teacher spread0.139 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainIncentives
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

Citations1
Published2024
Admission routes1
Has abstractyes

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