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Record W2909322228

Newspaper portrayal of mental illness in England, Canada, Portugal, Spain and Japan

2018· article· es· W2909322228 on OpenAlexaboutno aff
Empar Vengut Climent

Bibliographic record

VenueREVISTA ESPAÑOLA DE COMUNICACIÓN EN SALUD · 2018
Typearticle
Languagees
FieldSocial Sciences
TopicPublic Health and Social Inequalities
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperMental illnessMental healthPolitical scienceHumanitiesMedia coverageMedia studiesSociologyPsychologyPsychiatryArt
DOInot available

Abstract

fetched live from OpenAlex

espanolResearch concerning media portrayals of mental illnesses and the effects such portrayals might have on the public has usually been carried out within one country as a geographical limit. Herein, we analy­se the results of the research carried out through the analysis of newspapers in 5 different disperse countries around the world in the last decade; England, Canada, Portugal, Spain and Japan. Some of these countries have started national campaigns to reduce the stigmatisation of these conditions, including a focused awareness on Mental Health communication in media. Despite the heterogenicity of the societies studied and the different measures adopted, there is still a negative portrayal of mental illnesses in newspapers, which contributes to the ongoing mental illness stigmatisation. Other media also showed similar results. Moreover, this review intends to give a general vision on how research in this area is carried out and propose a reflection on how it should be pursued. EnglishLa investigacion relacionada con la imagen que los medios de comunicacion proporcionan de las enfermedades mentales y los efectos que esta imagen tiene en el publico se suelen realizar dentro de un pais como frontera geografica. En esta revision se analizan los resultados obte­nidos en diferentes estudios que analizan la cobertura de la salud mental en periodicos de 5 paises diferentes, Inglaterra, Canada, Portugal, Espana y Japon. Algunos de estos paises han lanzado campanas a nivel nacional para reducir el estigma relacionado con estas enfermedades y presentan una parte focalizada en la comunicacion de la salud mental por parte de los medios de comunicacion. A pesar de la diversidad de las sociedades estudiadas y de las diferentes medidas tomadas en cada uno de estos paises, sigue habiendo una representacion negativa de las enfermedades mentales en los periodicos, lo que contribuye a la perpetuacion del estigma. Ademas, se han obtenido resultados semejantes en otros medios. Finalmente, esta revision intenta dar una perspectiva general de como se llevan a cabo este tipo de investigaciones y propone una reflexion de como deberia de ser.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.323
Teacher spread0.306 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2018
Admission routes1
Has abstractyes

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