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Record W4239109852 · doi:10.3410/f.1010229.240494

Faculty Opinions recommendation of Do the print media "hype" genetic research? A comparison of newspaper stories and peer-reviewed research papers.

2004· dataset· en· W4239109852 on OpenAlexfundno aff
James F. Gusella

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2004
Typedataset
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaGenome PrairieFondation pour la Recherche MédicaleUniversity of AlbertaStem Cell Network
KeywordsNewspaperFraming (construction)Political scienceHistoryLaw

Abstract

fetched live from OpenAlex

BACKGROUND: The public gets most of its information about genetic research from the media. It has been suggested that media representations may involve exaggeration, called "genohype." To examine the accuracy and nature of media coverage of genetic research, we reviewed the reporting of single-gene discoveries and associated technologies in major daily newspapers in Canada, the United States, Great Britain and Australia.METHODS: We used neutral search terms to identify articles about gene discoveries and associated technologies hosted on the Dow Jones Interactive and Canadian NewsDisk databases from January 1995 to June 2001. We compared the contents, claims and conclusions of the scientific journal article with those of the associated newspaper article. Coders subjectively assigned the newspaper articles to 1 of 3 categories: moderately to highly exaggerated claims, slightly exaggerated claims or no exaggerated claims. We used classification tree software to identify the variables that contributed to the assignment of each newspaper article to 1 of the 3 categories: attention structure (positioning in the newspaper and length of the article), authorship, research topic, source of information other than the scientific paper, type and likelihood of risks and benefits, discussion of controversy, valuation tone (positive or negative), framing (e.g., description of research, celebration of progress, report of economic prospects or ethical perspective), technical accuracy (either omissions or errors that changed the description of the methods or interpretation of the results) and use of metaphors.RESULTS: We examined 627 newspaper articles reporting on 111 papers published in 24 scientific and medical journals. Only 11% of the newspaper articles were categorized as having moderately to highly exaggerated claims; the majority were categorized as having no claims (63%) or slightly exaggerated claims (26%). The classification analysis ranked the reporting of risks as the most important variable in determining the categorization of newspaper articles. Only 15% of the newspaper articles and 5% of the scientific journal articles discussed costs or risks, whereas 97% of the newspaper articles and 98% of the scientific journal articles discussed the likelihood of benefits of the research.INTERPRETATION: Our data suggest that the majority of newspaper articles accurately convey the results of and reflect the claims made in scientific journal articles. Our study also highlights an overemphasis on benefits and under-representation of risks in both scientific and newspaper articles. The cause and nature of this trend is uncertain. PMID: 15111473

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)0.003
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.997
Threshold uncertainty score0.387

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.017
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1160.062

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 head0.488
GPT teacher head0.567
Teacher spread0.079 · 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.

Study designObservational
DomainReporting
GenreDataset

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

Citations0
Published2004
Admission routes1
Has abstractyes

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