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.
Bibliographic record
Abstract
1. Most people in the developed world agree on what 'animal welfare' is, although it is impossible to give it a precise scientific definition. 2. The argument is made that animal welfare is all to do with the feelings of animals and not the primary needs that these feeling have evolved to protect. 3. Acceptance of subjective feelings as a legitimate subject for scientific investigation has a long and well-established history in science. This acceptance was interrupted by the rise of Behaviorism in the 20th century, but now seems to be re-established. 4. Subjective feelings cannot be studied directly. However, in the animal welfare debate, indirect evidence on feelings is extremely useful, and methods for obtaining this indirect evidence are described. 5. The poultry species are capable of feeling several states of suffering including fear, frustration and pain. A start has been made to elucidate these states and the conditions that cause them, but much remains to be done. Recent evidence suggests that the poultry species may also be capable of experiencing pleasure. 6. It is concluded that, although poultry welfare is all to do with the subjective feelings of the birds, it is possible to be objective and scientific about these feelings. Investigation into poultry welfare, therefore, really is science rather than subjectivity.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it