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Record W2146850953

Framing Homelessness for the Canadian Public: The News Media and Homelessness

2011· article· en· W2146850953 on OpenAlexaboutno aff
Moira J. Calder, Alberta Hansard, Solina Richter, Katharina Kovacs Burns, Yuping Mao

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsFraming (construction)NewspaperMedia studiesNews mediaSociologyPolitical sciencePublic relationsHistory
DOInot available

Abstract

fetched live from OpenAlex

In Canada newspapers remain a signifi cant source of information available to the public. However, little research has been done on Canadian news media representations of homelessness and their refl ection of or infl uence on social norms and values. In this paper the authors review the literature exploring news media depictions of homelessness from the perspectives of news framing, media infl uence on social norms and values, and the construction of news. Examples from Canadian newspapers are provided to demonstrate the media’s framing and portrayal of people who are homeless or their issues and circumstances. In relation to the framing of the homeless and their situations, the authors describe four primary factors that infl uence the media in their selection of frames. The paper concludes with targeted analysis about the importance of understanding how and why the media frame their stories about the homeless as they do, and what further research is needed.

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)0.005
metaresearch head score (Gemma)0.013
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 score0.095
Threshold uncertainty score0.690

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.011
Science and technology studies0.0230.015
Scholarly communication0.0180.006
Open science0.0020.005
Research integrity0.0020.003
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 head0.108
GPT teacher head0.347
Teacher spread0.238 · 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
Published2011
Admission routes1
Has abstractyes

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Same venueData Archiving and Networked Services (DANS)Same topicHomelessness and Social IssuesFrench-language works237,207