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Record W3021210146 · doi:10.25200/bjr.v16n1.2020.1104

HEALTHY EATING IN THE PRESS: using Morin-Chartier’s content analysis in a Brazilian newspaper

2020· article· en· W3021210146 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBrazilian Journalism Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMedia and Communication Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsNewspaperPortugueseSubject (documents)Content analysisHumanitiesLibrary scienceAdvertisingSociologyComputer scienceArtMedia studiesPhilosophySocial scienceBusinessLinguistics

Abstract

fetched live from OpenAlex

This paper evaluates if Morin-Chartier’s content analysis, when adapted to Portuguese, can successfully be applied to texts on health and diet published in a Brazilian newspaper. This is a cross-section study. The texts were collected from the Brazilian newspaper O Dia between January 2014 and July 2015. Texts written on the subject of health and diet were analyzed, and specific software was used to evaluate how often they appeared in various categories. The method demonstrably categorizes and classifies different subjects within a single text, and thus helping to minimize any errors. A total of 1.668 information units were extracted from a collection of 341 journalistic texts. These information units focused on the effects foods have on the body and recommendations for which foods to consume. Most of these foods were in natura but there were some ultra-processed as well. The texts are taken from the Brazilian press, and the sources, when identified, are specialists on the subject. The texts are written with the intent to promote health.A pesquisa avalia a aplicabilidade do método canadense de análise de conteúdo de Morin-Chartier em textos sobre saúde e alimentação, apresentados pelo jornal popular brasileiro O Dia, entre janeiro de 2014 e julho de 2015. A análise se baseia no registro das unidades da informação na imprensa que tratam sobre o tema alimentação, e avaliação de sua frequência em diferentes categorias com produção e uso de software específico. O método possibilitou que diferentes assuntos no mesmo texto fossem categorizados e classificados distintamente, minimizando falhas. Dos 341 textos jornalísticos coletados, extraiu-se 1.668 unidades da informação, observando enfoque em recomendações e efeitos dos alimentos, com maior presença dos in natura em detrimento dos ultraprocessados. A origem dos textos é nacional e as fontes, quando identificadas, são especializadas, em sua maioria. O engajamento dos textos é favorável à saúde. La investigación adapta al português y evalua la aplicabilidade de um método canadiense de análisis de contenido de Morin Chartier, en textos sobre salud y alimentación presentados por um periódico popular brasileño, O Dia, entre enero de 2014 y julio de 2015. La análisis es basada en el registro de las unidades de información que hablan del tema alimentación, e evaluación de su frecuencia de diferentes categorías con producción y uso de software específico. La metodología posibilita que diferentes temas en un mesmo texto sean categorizados y clasificados distintamente, minimizando fallas. De los 341 artículos, se observó 1.668 unidades de la información, observando el foco en las recomendaciones y efectos de los alimentos, com más frecuencia de los alimentos naturales. La origen de los textos es brasileña, y las fuentes identificadas son en gran parte, especializadas; el engajamento de los textos es favorable a la salud.

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.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.192
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.514
GPT teacher head0.500
Teacher spread0.015 · 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