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Record W160845876

Sex trafficking discourse and the 2010 Olympic Games

2013· dissertation· en· W160845876 on OpenAlexaboutno aff
Dalia Vukmirovich

Bibliographic record

VenueSummit (Simon Fraser University) · 2013
Typedissertation
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsnot available
Fundersnot available
KeywordsSex traffickingPolitical scienceGender studiesAdvertisingHuman traffickingCriminologyPsychologySociologyBusiness
DOInot available

Abstract

fetched live from OpenAlex

This thesis looks at how sex trafficking was constructed as a social problem by certain groups in the context of the 2010 Winter Olympics held in Vancouver, and examines what effects the Games were perceived to have on issues related to sex trafficking. The study is conducted as a qualitative, two-phase sequential multi-method project. Using participant observation and interview data, I argue that the concerns about sex trafficking were raised to problematize the male demand for commercial sex and call for abolition of prostitution in Canada through adoption of the Nordic legal model, which criminalizes those who purchase sex and decriminalizes those who sell it. While there has been no evidence to suggest that sex trafficking was an issue during the Olympics, the raising of the related concerns had important consequences. It shifted the understanding of prostitution toward that of sex trafficking, while relying on a discourse reflective of ideological positions that see women in the sex trade as victims who need to be protected.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.480
Threshold uncertainty score0.965

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0280.018
Scholarly communication0.0090.002
Open science0.0010.005
Research integrity0.0030.003
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 head0.010
GPT teacher head0.249
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
Published2013
Admission routes1
Has abstractyes

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