MétaCan
Menu
Back to cohort

Weighing Health Benefit and Health Risk Information when Consuming Sport‐Caught Fish

2003· article· en· W2023780179 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRisk Analysis · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsnot available
FundersNew York Sea Grant, State University of New YorkResearch Foundation for the State University of New YorkNational Oceanic and Atmospheric AdministrationU.S. Department of Commerce
KeywordsEnvironmental healthConsumption (sociology)PopulationPublic healthFish <Actinopterygii>Health riskHealth benefitsMedicineFisheryNursing

Abstract

fetched live from OpenAlex

Fish consumers may incur benefits and risks from eating fish. Health advisories issued by states, tribes, and other entities typically include advice about how to limit fish consumption or change other behaviors (e.g., fish cleaning or cooking) to reduce health risks from exposure to contaminants. Eating fish, however, may provide health benefits. Risk communicators and fish consumers have suggested the importance of including risk comparison information, as well as health risk-benefit comparisons in health advisory communications. To improve understanding about how anglers fishing in waters affected by health advisories may respond to such risk-risk or risk-benefit information, we surveyed Lake Ontario (NY, USA) anglers. We interviewed by telephone 4,750 anglers, 2,593 of which had fished Lake Ontario in the past 12 months and were sent a detailed mail questionnaire (1,245 responded). We posed questions varying the magnitude of health risks and health benefits to be gained by fish consumption, and varied the population affected by these risks and benefits (anglers, children, women of childbearing age, and unborn children). Respondents were influenced by health benefit and health risk information. When risks were high, most respondents would eat less fish regardless of the benefit level. When risks were low, the magnitude of change in fish consumption was related to level of benefit. Responses differed depending on the question wording order, that is, whether "risks" were posed before "benefits." For a given risk-benefit level, respondents would give different advice to women of childbearing age versus children, with more conservative advice (eat less fish) provided to women of childbearing age. Respondents appeared to be influenced more strongly by risk-risk comparisons (e.g., risks from other foods vs. risks from fish) than by risk-benefit comparisons (e.g., risks from fish vs. benefits from fish). Risk analysts and risk communicators should improve efforts to include risk-risk and risk-benefit comparisons in communication efforts, and to clarify to whom the health risks and benefits from fish consumption may accrue.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.312
Teacher spread0.294 · 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