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Record W7036321014

Broadening the story: the beginnings of a peopleâs history of sport in Canada

2018· article· en· W7036321014 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2018
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsnot available
Fundersnot available
KeywordsHistoriographyMainstreamNarrativePublic historyConstruct (python library)Oral historyPresentation (obstetrics)
DOInot available

Abstract

fetched live from OpenAlex

In The Twentieth Century: A People’s History, Howard Zinn (2003: x) asserts that “If history is to be creative, to anticipate a possible future without denying the past, it should, I believe, emphasize new possibilities by disclosing those hidden episodes of the past when, even if in brief flashes, people showed their ability to resist, to join together, occasionally to win.” The historiography of Canadian sport still privileges dominant institutions and mainstream sports/leagues, overlooking the experiences of many. The larger project of which this paper is a component takes up Zinn’s call, in an effort to (re)map the landscape of Canadian sport history and broaden our understanding of the ways in which people express themselves through sport and re-conceptualize the lived experiences of sport. The beginning of a People’s History of Canadian sport focused on the history of sport in African Nova Scotian communities, with particular attention paid to the community of Africville. Archives were consulted, oral history interviews were conducted, and privately held documents were accessed, while museum exhibits considered the public presentation of African Nova Scotian sport history. This paper attempts to bring some coherence to these diverse historical sources, but does so in consideration of the methodological challenges of such an effort, of trying to construct a narrative, and do justice to an under-told narrative, through empirical gaps. Moreover, it explores the theoretical questions of the historian’s outsider status within a community as well as who has ownership of this narrative and the right to tell it.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.007
Science and technology studies0.0730.026
Scholarly communication0.0180.006
Open science0.0020.007
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0080.000

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 head0.026
GPT teacher head0.206
Teacher spread0.180 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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