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Record W4386743443 · doi:10.3390/ani13182913

To Treat or Not to Treat: Public Attitudes on the Therapeutic Use of Antibiotics in the Dairy Industry—A Qualitative Study

2023· article· en· W4386743443 on OpenAlexaff
K.F. Knowlton, M.A.G. von Keyserlingk

Bibliographic record

VenueAnimals · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLicenseQualitative researchPromotion (chess)AntibioticsMedicinePsychologyFamily medicineSociologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

This paper describes the views of 779 U.S. residents on questions related to therapeutic antibiotic use in dairy cattle. An online survey was conducted with qualitative (open-ended) questions. Respondents were offered one of three scenarios with varying degrees of information describing a farmer with a sick cow that would benefit from antibiotic therapy. The text replies to the open-ended questions were analyzed by grouping responses with similar comments and identifying patterns or themes. Content analysis showed that many of the participants in this study provided farmers with the social license to treat sick cows with antibiotics; however, some participants commented on the social license not necessarily extending to antibiotic use for growth promotion or prophylactic use. Our findings are not generalizable, but may provide some insight that should be considered when developing policies and practices regarding the use of antibiotics on dairy farms that may promote improved alignment with societal values.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.322
GPT teacher head0.445
Teacher spread0.122 · 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 designObservational
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

Citations4
Published2023
Admission routes1
Has abstractyes

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