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Record W2088004187 · doi:10.3138/jvme.37.1.74

Educating the Public: Information or Persuasion?

2010· article· en· W2088004187 on OpenAlexvenueno aff
Grahame J. Coleman

Bibliographic record

VenueJournal of Veterinary Medical Education · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsPersuasionPublic relationsWelfareSustainabilityAnimal welfareBusinessPolitical scienceProcess (computing)Mass mediaPublic economicsPsychologySocial psychologyEconomicsLaw

Abstract

fetched live from OpenAlex

Beliefs form a major component of public attitudes, and attitudes have a role in determining how people behave as consumers and as citizens. Their behavior in turn affects the commercial viability and even the sustainability of animal industries. Beliefs are subjective facts, that is, matters that individuals consider to be true. The process of informing the community necessarily involves changing beliefs and, to this extent, persuasion. Education strategies relating to welfare issues depend on the target group and the desired outcome. Target groups include farmers, post-farm gatekeepers including transport drivers and abattoir workers, carers of companion animals, legislators and regulators, retailers, and the general community. These target groups may not be homogeneous, but each nevertheless has identifiable needs for knowledge and skills relevant to welfare. The approach that is likely to be most effective is to provide appropriately targeted dispassionate and factual information to the community. In this way, when debates about animal welfare occur, all the stakeholders--including animal-rights groups, retailers, farmers, legislators, and regulators--who are involved in the debate are more likely to produce good outcomes if discussion is based on a shared understanding of what current practices are and what science can reveal about welfare. Given that the mass media are the preferred source of information, the use of science-based media coverage and informed ethical debate is likely to have the best effect, albeit over a fairly long time frame.

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)0.004
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.890
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0220.000

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 head0.025
GPT teacher head0.340
Teacher spread0.315 · 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 designOther design
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

Citations36
Published2010
Admission routes1
Has abstractyes

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