HEALTHY EATING IN THE PRESS: using Morin-Chartier’s content analysis in a Brazilian newspaper
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.020 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".