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Record W2227470048 · doi:10.1177/1742715015586215

The perceived impact of sexual orientation on the ability of queer leaders to relate to followers

2015· article· en· W2227470048 on OpenAlexaff
Jerome Chang, Michèle A. Bowring

Bibliographic record

VenueLeadership · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsQueerSexual orientationWorkforceQualitative researchPublic relationsContext (archaeology)Diversity (politics)Social psychologySociologyPsychologyGender studiesPolitical scienceSocial science

Abstract

fetched live from OpenAlex

As the body of research around diversity and leadership in the workforce continues to grow and develop, so does research around the queer experience in the workforce. Thus far, a great deal of research on the queer experience focuses on the costs and benefits of disclosure in the workplace. However, little work explores the intersection of leadership and sexual orientation. The aim of this qualitative paper is to focus on the specific work and/or volunteer leadership experiences of queer leaders within the context of their organizations. In particular, we focus on how queer leaders perceive the impact of their sexual orientation on their ability to relate to followers. Among the identified themes, issues of disclosure, advocacy, and temporal placement were the most consistent areas perceived to be impacted by sexual orientation. The implications and limitations of this study for future research 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 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)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.004
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.400
GPT teacher head0.386
Teacher spread0.014 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations27
Published2015
Admission routes1
Has abstractyes

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