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Record W2931639476 · doi:10.1177/1741659019838003

Claims-making, child saving, and the news media

2019· article· en· W2931639476 on OpenAlexaffabout
Steven Kohm

Bibliographic record

VenueCrime Media Culture An International Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsFraming (construction)NewspaperChild sexual abuseLegislatureSocial mediaPolitical sciencePublic relationsRhetoricSociologyStrict constructionismAgency (philosophy)Making-ofThe InternetMedia studiesAdvertisingLawSocial scienceSexual abuseBusinessEngineeringPoison control

Abstract

fetched live from OpenAlex

Drawing on a social constructionist paradigm, this article critically examines mass-mediated framing of the issue of child sexual exploitation online and via mobile communications technology. The Canadian Centre for Child Protection (C3P), 1 a non-profit charity located in Winnipeg, Canada, is used as a case study of claims-making and the social construction of the social problem of child sexual exploitation online. The present study focuses on media engagement by C3P and its subsidiary CyberTip—Canada’s national internet tip line—between 2000 and 2011, just prior to CyberTip receiving legislative designation as Canada’s official reporting agency. The analysis draws on news media accounts of claims-making activities of C3P in three local and national Canadian newspapers. By focusing on the rhetoric of claims forwarded by the organization, I argue that C3P has been successful in gaining symbolic ownership of the issue and has been instrumental in defining the nature, extent, and appropriate responses to the problem of online child sexual exploitation in Canada. I conclude by considering the broader implications for criminal justice policy and practice.

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)0.008
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.287
Threshold uncertainty score0.570

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.005
Science and technology studies0.0240.067
Scholarly communication0.0220.009
Open science0.0020.007
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.320
Teacher spread0.305 · 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 designObservational
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

Citations8
Published2019
Admission routes2
Has abstractyes

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