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Record W2419101820 · doi:10.1093/ahr/121.3.949

J. Andrew Ross.<i>Joining the Clubs: The Business of the National Hockey League to 1945</i>.

2016· article· en· W2419101820 on OpenAlexaboutno aff
Craig R. Coenen

Bibliographic record

VenueThe American Historical Review · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAmateurLeagueIce hockeyPopularityChampionshipEliteAdvertisingPolitical scienceRevenueBig businessSpectator sportMarketingBusinessEngineeringManagementEconomicsAccountingLaw

Abstract

fetched live from OpenAlex

As social, economic, and technological changes made it possible for the development and growth of ice hockey, sportsmen guided the game from humble, disorganized beginnings to form amateur clubs, create rules and uniform standards of play, and establish elite teams with widespread appeal. Growth and popularity allowed businessmen to see opportunities to professionalize ice hockey. Joining the Clubs: The Business of the National Hockey League to 1945 describes the creation, growth, and establishment of ice hockey as a profitable and meaningful professional sport in North America from 1875 through 1945. Ice hockey developed over four decades before the National Hockey League (NHL) formed. In those years, the rules, equipment, and style of play standardized and the “Montreal game” (16) spread all across Canada and into the U.S. Ice-making technology in the 1890s facilitated extended seasons and broadened the game’s scope to warmer climates. Amateur clubs and leagues sprung up. By the 1890s, teams were vying for a championship trophy—the Stanley Cup. The desire for strong teams, the sport’s popularity and commercial possibilities, and the need to meet costs for ice-making, indoor rinks, travel, and other expenses led increasingly to professionalizing hockey. Deals with sporting goods companies and sponsorships generated revenue, but compensating the best players became common practice. Hockey underwent a gradual, but not universal, acceptance of professionalism. Even some leagues dropped amateur from their names.

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.086
Threshold uncertainty score0.286

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0860.041

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 head0.257
Teacher spread0.211 · 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
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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