MétaCan
Menu
Back to cohort
Record W4393239877 · doi:10.1123/shr.2023-0023

Carving Out Spaces of Resistance: Remembering Women’s Ski Jumping, Gendered Spaces, and Built Environments at Canada Olympic Park, 1987–2019

2024· article· en· W4393239877 on OpenAlexaffabout
Charlotte Mitchell

Bibliographic record

VenueSport History Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCarvingResistance (ecology)Gender studiesSociologyArtVisual arts

Abstract

fetched live from OpenAlex

This article examines the history of Canada Olympic Park (COP) as it transitioned from the Paskapoo Slopes to a venue for the Calgary 1988 Winter Olympic Games and how the site framed the fight for gender equality in the sport by women ski jumpers in Canada. Ski jumping is a sport that can be considered a “nature sport” as it is practiced in the open air while simultaneously relying on built environments. Understanding the COP ski jumping venue as a “sportscape” and a gendered landscape provides a unique opportunity to explore the tensions between land, air, and the body in this nature sport. Historical analysis of the XV Winter Olympic Games inventories held at the City of Calgary Archives is combined with autoethnographic reflections of my past experiences as a ski jumping athlete who trained at the COP ski jumping venue and plaintiff in the court case to get a women’s ski jumping event added to the 2010 Winter Olympic Games to frame my analysis. This paper argues that women ski jumpers at COP carved out spaces of resistance for themselves, shifted the gendered landscape of the ski jumps, and effected change across generations of women ski jumpers on and off the hill.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.100
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0050.007
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.002
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 head0.035
GPT teacher head0.276
Teacher spread0.241 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueSport History ReviewSame topicSport and Mega-Event ImpactsFrench-language works237,207