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Record W4414065608 · doi:10.1080/14927713.2025.2551516

That is not my job: a critical content analysis of how social justice leadership concepts are (un/under)used within community recreation job descriptions of the Greater Toronto and Hamilton Area

2025· article· en· W4414065608 on OpenAlexvenueaboutno aff
Jordan O’Dell

Bibliographic record

VenueLeisure/Loisir · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsSocial justiceContent analysisRecreationSocial analysisContent (measure theory)Organizational justice

Abstract

fetched live from OpenAlex

This study explored how social justice leadership concepts are taken up in existing community recreation practitioner job postings in the Greater Toronto and Hamilton Area. A critical content analysis based in social justice leadership concepts was used to conduct deductive coding and analysis of 21 job descriptions. This analysis process generated insights about both manifest (words in text used) and latent (underlying meaning of words) content. For manifest content, the social justice leadership terms most used in the sample were diversity, inclusion, equity, and accessibility. For latent content, two themes emerged: (1) Status Quo Leadership Over Social Justice Leadership and (2) Omission of Core Social Justice Commitments: Praxis and Intersectional Responsiveness. Two recommended paths are proposed for practitioners to enhance the use of social justice leadership concepts in job descriptions: rethinking the who and rethinking the how. Future research directions are summarized in conversation with the study’s strengths and limits.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.319
GPT teacher head0.378
Teacher spread0.059 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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