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Record W1833083513 · doi:10.1080/17512780903429829

HELP OR HARM?

2010· article· en· W1833083513 on OpenAlexaboutno aff
Linda Kay, Rosemary C. Reilly, Kate Connolly, Stephen L. Cohen

Bibliographic record

VenueJournalism Practice · 2010
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsGriefHarmSuspectWitnessAngerCriminologyTragedy (event)CriminalizationSociologyPraxisPsychologySocial psychologyPolitical scienceLawSocial sciencePsychotherapist

Abstract

fetched live from OpenAlex

This paper describes the impact of extensive journalistic coverage on a small community in Quebec that experienced the murder of a teenage girl by a local man. Press coverage of the case was intense, as journalists converged on the small rural town to cover the story and the subsequent arrest of the suspect and his parents. In presenting the voices of both local residents and a journalist, this paper illuminates the secondary trauma and symbolic violence that can result from some forms of news coverage of a traumatic event. Five key themes regarding the impact of the media on community residents arose from the data: alienation from the community, anger at the media's public construction of the community, intrusion on community life, intrusion on the private processes of grief, and triggering renewed feelings of loss and grief. Implications for journalists are discussed, including being aware of the dynamics of symbolic violence and secondary trauma and incorporating positionality, empathy, and reflective practice into their reporting praxis.

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)0.011
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: none
Teacher disagreement score0.036
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.009
Scholarly communication0.0050.005
Open science0.0010.005
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0360.011

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 head0.044
GPT teacher head0.391
Teacher spread0.347 · 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

Citations27
Published2010
Admission routes1
Has abstractyes

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