Establishing consensus on the best ways to educate children about animal welfare and prevent harm: An online Delphi study
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
Abstract Many animal welfare organisations deliver education programmes for children and young people, or design materials for schoolteachers to use. However, few of these are scientifically evaluated, making it difficult for those working in this field to establish with any certainty the degree of success of their own programmes, or learn from others. There has been no guidance specifically tailored to the development and evaluation of animal welfare education interventions. Accordingly, a three-stage online Delphi study was designed to unearth the expertise of professionals working in this field and identify degree of consensus on various aspects of the intervention process: design, implementation and evaluation. Thirty-one experts participated in Round 1, representing eleven of 13 organisations in the Scottish Animal Welfare Education Forum (SAWEF), and eleven of 23 members of the wider UK-based Animal Welfare Education Alliance (AWEA). Seven further professionals participated, including four based in Canada or the US. Eighty-four percent of the original sample participated in Round 2, where a high level of consensus was apparent. However, the study also revealed areas of ambiguity (determining priorities, the need for intervention structure and degree of success). Tensions were also evident with respect to terminology (especially around cruelty and cruelty prevention), and the common goal for animal welfare to be part of school curricula. Findings were used to develop a web-based framework and toolkit to enable practitioners to follow evidence-based guidance. This should enable organisations to maximise the quality and effectiveness of their interventions for children and young people.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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