Farm Animal Behaviour — Characteristics for Assessment of Health and Welfare
Bibliographic record
Abstract
The author of this comprehensive, but not exhaustive, undergraduate level text demonstrates thorough knowledge of his subject and current world literature, with the inclusion of over 670 references in this work, many authors known to us in Canada for their studies in animal welfare over the preceding 3 to 4 decades. The book is well-organized in 3 sections, covering horses, cattle, swine, sheep, and goats in part I, poultry and farmed birds in part II, and non-domesticated deer to include only fallow and red deer in part III. Quality illustrations in black and white clearly complement points discussed in the text. Not covered are other deer species currently farmed on the NA continent, bison or alpaca, although much is known of their natural behavior, and as farming enterprises. Consideration might be given to the inclusion of these animals in a future edition. Each chapter follows a consistent pattern describing the behavioral characteristics of the species featured. Reference is made to the natural state before domestication, leading us through the various changes to the present, demonstrating along the way recognized behavioral needs of animals subject to modern management systems. Innate, learned, and social behaviors, activity patterns, senses, behavior in the young animal, vision and hearing, mating, pregnancy, birthing, and mothering are chronicled for each animal species within natural and artificial settings. Clearly, the pendulum has swung far in favor of production oriented systems of animal management considering the behavioral needs of animals, and often at odds with them and optimal welfare. By example, the author demonstrates problems currently encountered due this emphasis, leading us to look at the normal, enabling recognition of the abnormal. Ekesbo has a great ability to encourage the reader to think about what is written, coming to one’s own conclusions. Many influences affect our judgement, reasonable and unreasonable, today. This is a book of observation and truth, of great worth to anyone in a caring or advisory role. Those who have managed the animals and birds covered over a period of several decades will acknowledge what they have learned in the field is now documented in print; for those now entering the world of animal agriculture, author Ekesbo has done them a great favor with the publication of this text!
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".