Using physical and emotional parameters to assess donkey welfare in Botswana
Bibliographic record
Abstract
INTRODUCTION: Working donkeys in Maun, Botswana contribute to people's livelihoods substantially through the provision of transport, ploughing and income generating activities. However, working donkeys suffer from various welfare issues that were investigated in this study to provide preliminary insights on their health and well-being. MATERIALS AND METHODS: An assessment protocol involving direct observations of the donkeys was developed and operationalised to assess physical and emotional welfare. Physical welfare parameters such as body condition score, abnormal limbs, impeded gait, eye abnormalities, sore and scar locations, hoof and coat condition were recorded. Emotional welfare parameters such as eyes, tail movement, ear position, neck position, posture and vocalisation were recorded. In addition, donkey-owner interactions were recorded and scored, as well as the donkey's response to environmental factors. A total cross-section of 100 donkeys sub-stratified by roles of riding, cart pulling and resting were randomly selected in eight villages and three urban wards and assessed during the period of May to August 2012. RESULTS: The findings reveals that the 100 adult working donkeys assessed were physically afflicted by poor BCSs of two (66 per cent), long and cracked hooves (50 per cent), sores on at least two locations on their body (53 per cent), scars on at least two locations on their body (86 per cent), and poor coat conditions (58 per cent). Emotionally, donkeys displayed unresponsiveness (35 per cent), avoidance (31 per cent), disinterest in hand sniffing (59 per cent), dull facial expression (33 per cent), tail stillness (89 per cent), neck stiffness and/or raised head (13 per cent) or head hanging low (32 per cent visibly withdrawn), and tense ears pointing back or to the side (69 per cent). By contrast, the remaining donkeys (31 per cent) exhibited a happy demeanour of curiosity, interest, alert facial expression, tail swishing, relaxed ears pointed to the side or forward and neck relaxed and/or level. CONCLUSIONS: This study offers preliminary findings from an investigation into the welfare of working donkeys in Greater Maun, Botswana, and provides baseline research to inform future research and strategies to enhance donkey well-being.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".