MétaCan
Menu
← Back to cohort
Record W2475675711 · doi:10.1057/9780230367463_9

The XXI Olympiad: Canada’s Claim or Montreal’s Gain?: Political and Social Tensions Surrounding the 1976 Montreal Olympics

2012· book-chapter· en· W2475675711 on OpenAlexaboutno aff
Terrence Teixeira

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2012
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsOlympiadPoliticsPolitical scienceMedia studiesSociologyHistoryLawArchaeology

Abstract

fetched live from OpenAlex

May 12, 1970 was a day of dual significance for the city of Montreal. This was the day that Montreal was awarded the Games of the 21st Olympiad, the first Canadian city to host the Games. It was also on this day that Liberal Leader Robert Bourassa became Quebec’s 22nd premier. These two portentous events symbolised the unholy union of politics and sports. From that day forward, a bitter clash arose between all three levels of government in Canada - federal, provincial, and municipal - over the planning, organising and ownership of the Games. Although it is widely known that the Montreal Olympics were plagued with issues of mismanagement and overspending, the critical factors that led to this financial fiasco have not been as thoroughly explored. This chapter will examine how the fiscal disarray of the Montreal Games was exacerbated by the politics of Canadian federalism in the 1970s, and how in turn these Games changed the landscape of the Olympic Movement. The Games emerged as a source of tension in the Canadian political system as the federal government, province of Quebec and city of Montreal all attempted to leverage the Games for their own political gain. What was supposed to be the most modest of Games quickly turned into a spending spree and arguably resulted in the Montreal Olympics being better remembered for its billion-dollar debt rather than its electric 15 days of sport. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.091
Threshold uncertainty score0.662

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0230.010
Scholarly communication0.0120.003
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0160.001

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 head0.048
GPT teacher head0.287
Teacher spread0.239 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venuePalgrave Macmillan UK eBooks→Same topicSport and Mega-Event Impacts→French-language works237,207→