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Record W4291746628 · doi:10.1079/9781780644677.0125

The importance of good stockmanship and its benefits to animals.

2015· book-chapter· en· W4291746628 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.

Bibliographic record

VenueCABI eBooks · 2015
Typebook-chapter
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsProductivityAnimal welfareProduction (economics)WelfareMilk productionPsychologyAnimal scienceEconomicsBiologyEconomic growthEcologyMarket economyMicroeconomics

Abstract

fetched live from OpenAlex

Good stockmanship will improve both animal welfare and productivity. Dairy cows, pigs, and other animals that are fearful of people will have lower weight gain, lower milk production, and poorer reproductive productivity. Farms where animals are willing to approach people may be more productive. This chapter reviews many studies that clearly show the relationship between aversive (bad) treatment and lower production. Animals that have been hit or shocked may become fearful of all people. Stockpeople who have a positive attitude towards animals often have animals with increased productivity. Studies also show how training can be used to improve the attitudes of stockpeople. The animal's relationship with the stockperson is not the only factor that determines productivity. Farm cleanliness and a stockperson's attention to good management practices is also extremely important. To help stockpeople maintain a positive attitude, they must not be worked to the point of becoming exhausted.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.153
GPT teacher head0.334
Teacher spread0.181 · 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