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Record W2589237773 · doi:10.3168/jds.2016-11977

Invited review: Determinants of farmers' adoption of management-based strategies for infectious disease prevention and control

2017· review· en· W2589237773 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Dairy Science · 2017
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsUniversity of GuelphUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaDairy Farmers of ManitobaDairy Farmers of Canada
KeywordsBusinessControl (management)MarketingAgricultureCitizen journalismPublic relationsEconomicsPolitical science

Abstract

fetched live from OpenAlex

The prevention and control of endemic pathogens within and between farms often depends on the adoption of best management practices. However, farmers regularly do not adopt recommended measures or do not enroll in voluntary disease control programs. This indicates that a more comprehensive understanding of the influences and extension tools that affect farmers' management decisions is necessary. Based on a review of relevant published literature, we developed recommendations to support policy-makers, industry representatives, researchers, veterinarians, and other stakeholders when motivating farmers to adopt best management practices, and to facilitate the development and implementation of voluntary prevention and control programs for livestock diseases. Farmers will make management decisions based on their unique circumstances, agricultural contexts, beliefs, and goals. Providing them with rational but universal arguments might not always be sufficient to motivate on-farm change. Implementation of recommended management practices is more likely if farmers acknowledge the existence of a problem and their responsibility to take action. The perceived feasibility and effectiveness of the recommended management strategy and sufficient technical knowledge further increase the likelihood of adequate adoption. Farmers will also weigh the expected advantages of a proposed change against the expected disadvantages, and these considerations often include internal drivers such as pride or the desire to conform with perceived standards. Extension tools and farmers' social referents (e.g., veterinarians, peers) not only provide technical information but also influence these standards. Whereas mass media have the potential to deliver information to a broad audience, more personal approaches such as participatory group learning or individual communication with farm advisors can enable the tailoring of recommendations to farmers' situations. Approaches that appeal to farmers' internal motivators or that unconsciously elicit the desired behavior will increase the success of the intervention. Collaboration among stakeholders, assisted by social scientists and communication specialists, is necessary to provide a context that facilitates on-farm change and transfers consistent messages across extension tools in the most effective way.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.084
GPT teacher head0.368
Teacher spread0.284 · 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