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Record W3035796073 · doi:10.1177/0891241620931908

Structural Inequality, Homelessness, and Moral Worth: Salvaging the Self through Sport?

2020· article· en· W3035796073 on OpenAlexafffundabout
Jordan Koch, Jay Scherer, Rylan Kafara

Bibliographic record

VenueJournal of Contemporary Ethnography · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of AlbertaMcGill University
FundersCanadian Institutes of Health Research
KeywordsUnderclassSociologyEthnographyContext (archaeology)IndigenousGender studiesEmbodied cognitionColonialismCriminologyPolitical scienceLawHistory

Abstract

fetched live from OpenAlex

This urban ethnography explores how a group of men experiencing homelessness collectively produced an economy of moral worth and socially beneficial labor within and through a weekly sport-for-development program in the distinct settler-colonial context of Edmonton, Alberta. For over two decades, weekly floor hockey games have been organized by local health workers as part of a broader sport-based intervention/corrective aimed, in part, at reforming Edmonton’s urban ‘underclass’, one that is decidedly Indigenous. Drawing upon three-years of ethnographic field notes and interviews with ten men aged 25–42 years, our analysis revealed how these weekly sporting interludes served as convivial, safe, and consistent events that nurtured the development of long-term meaningful relationships with other participants and social workers, as well as a genuine sense of community. The weekly floor hockey matches were, thus, powerful sites in the broader struggle for what David Snow and Leon Anderson (1993) have called “salvaging the self” for men who embodied a repertoire of trauma and who are regularly positioned as morally devalued subjects who lacked personal responsibility and self-governance.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.116
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.021
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.111
GPT teacher head0.340
Teacher spread0.228 · 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

Citations2
Published2020
Admission routes3
Has abstractyes

Explore more

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