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Record W633356 · doi:10.1007/bf01872752

The double-edged sword : defining prostitution in mainstream Canadian press

2001· dissertation· en· W633356 on OpenAlexaboutno aff
Ainsley Claire Chapman

Bibliographic record

VenueThe Journal of Membrane Biology · 2001
Typedissertation
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperMainstreamCriminologyContext (archaeology)IdeologySexual orientationSociologyMedia studiesSWORDPovertyPolitical sciencePerspective (graphical)Sample (material)Gender studiesPoliticsLawHistoryArtEngineering

Abstract

fetched live from OpenAlex

Relying on a sample of newspaper articles from The Toronto Star and The Montreal Gazette, this analysis examines the discourse through which prostitutes and prostitution are represented in the media. The sample (N = 52) is randomly chosen from 749 articles collected between 1993 and 1994. A measurement tool is developed and used to code the articles, based on the context through which prostitution is discussed. Based on this sample, the underlying discourse being communicated provides only two perspectives to understand prostitution: an offender orientation portraying prostitutes as a source of crime and threat to communities, and a victim orientation portraying prostitutes as victims of abuse and poverty. This limited and negative discourse fails to communicate an alternative perspective, namely an orientation that examines prostitution as work . By promoting only negative stereotypes the media effectively marginalizes prostitutes and defines prostitution as a social problem. Since prostitutes rarely participate in this public discourse about prostitution, the ideologies behind their movement for rights and respect can not be communicated.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.613
Threshold uncertainty score0.769

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.019
GPT teacher head0.317
Teacher spread0.298 · 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
Published2001
Admission routes1
Has abstractyes

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