MétaCan
Menu
Back to cohort
Record W2762264554 · doi:10.1386/public.27.53.22_1

The illusion of inclusion: Agenda 21 and the commodification of Aboriginal culture in the Vancouver 2010 Olympic Games

2016· article· en· W2762264554 on OpenAlexaffabout
Janice Forsyth

Bibliographic record

VenuePublic · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsWestern University
Fundersnot available
KeywordsCommodificationInclusion (mineral)NothingIndigenousPower (physics)Media studiesPolitical scienceSociologyGender studiesEconomy

Abstract

fetched live from OpenAlex

Abstract This article investigates the discourse about Aboriginal people benefitting from the 2010 Olympic Games and argues there was nothing fundamentally new about Aboriginal involvement in Vancouver, except for an unprecedented mobilization of Aboriginal bodies, land and insignia. In this regard, Aboriginal inclusion in 2010 was definitely different from past Games. There were more Aboriginal performers, artists and volunteers, more cultural imagery in strategic locations, and more indigenous merchandise for sale than ever before. Yet, in spite of their increased visibility, the power relations sustaining historic inequities between Olympic organizers and Aboriginal people remained largely unchanged. Indeed, a closer look at how Aboriginal people were involved in the Vancouver Games, the promises made to them, and the legacies that actually materialized, suggests the present day arrangement for Aboriginal people within the Olympic industry has actually worsened.

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)0.006
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.832

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0280.049
Scholarly communication0.0190.003
Open science0.0010.011
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.313
Teacher spread0.287 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

Explore more

Same venuePublicSame topicSport and Mega-Event ImpactsFrench-language works237,207