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Record W4213162448 · doi:10.1080/09523367.2022.2037568

Estranged: Notes on the Historical Development of the Relationship between Players and Manufacturers of Ice Hockey Equipment in Canada

2022· article· en· W4213162448 on OpenAlexaffabout
Guilherme Nothen, Bruce Kidd

Bibliographic record

VenueThe International Journal of the History of Sport · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIce hockeyLeagueOutsourcingBusinessFactory (object-oriented programming)ManufacturingOperations managementMarketingEngineeringComputer science

Abstract

fetched live from OpenAlex

This inquiry seeks to address the historical development of the relationship between players and manufacturers of ice hockey equipment in Canada. It pays particular attention to three inter-related trends that have affected this relationship quite decisively. First, the monopolization of equipment standards, enabled by a convergence in the interests of emerging equipment companies and hockey leagues, as the hockey manufacturing industry consolidated a solid Canadian presence throughout the twentieth century. Second, the rise of offshoring and outsourcing strategies, which set in motion a wave of factory closures and layoffs – culminating in the rather paradoxical fact that, today, almost the totality of the ice hockey equipment consumed in Canada was produced in foreign lands. Finally, the article presents what research participants perceive as a significant change in the profile of the executives who run major hockey manufacturing companies, namely the replacement of those with direct hockey experience by financial experts. The study concludes that, together, these three trends combined to drive players and manufacturers of ice hockey equipment progressively apart. The piece closes with a brief analysis of the present situation as it relates to the hockey manufacturing industry in North America.

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)0.000
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 score0.383
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.047
GPT teacher head0.235
Teacher spread0.188 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

Explore more

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