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Record W3013357279 · doi:10.1080/14660970.2020.1742705

‘I’d like to think I’m a good referee’: discourses of ability and the subjectivity of the female soccer referee in Ontario (Canada)

2020· article· en· W3013357279 on OpenAlexaffabout
Kamiel Reid, Christine Dallaire

Bibliographic record

VenueSoccer and Society · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of OttawaMount Royal University
Fundersnot available
KeywordsSubjectivityCompetence (human resources)Subject (documents)Gender studiesSociologyPower (physics)Social psychologyPsychologyEpistemology

Abstract

fetched live from OpenAlex

Female officials are side-lined within the soccer community through gendered relations of power, even in Canada, where women remain outnumbered as referees and in other leadership positions despite remarkable growth in the women’s game since the 1980s and its heightened respect and standing. Drawing upon Foucault’s concepts of discourse and subject, we explored the experience of female referees who had persevered in their role for 2 years or more within the male-dominated ranks of referees and had been subjected to, and the subject of, discourses of ability that constructed their (perceived lack of) skill and competence as unbiased arbitrators on the soccer field. In making sense of their referee subjectivity, they constructed stories of ability according to (1) first experiences, (2) skill recognition and validation, (3) being ‘a good referee’, and (4) proving oneself, while simultaneously engaging with discourses of gender, albeit sparingly and not always purposefully.

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)0.009
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 score0.098
Threshold uncertainty score0.712

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0560.043
Scholarly communication0.0130.005
Open science0.0030.009
Research integrity0.0040.007
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 head0.032
GPT teacher head0.273
Teacher spread0.241 · 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

Citations15
Published2020
Admission routes2
Has abstractyes

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