<i>Becoming care-full</i> : contextualizing moral development among captive elephant volunteer tourists to Thailand
Bibliographic record
Abstract
Tourism literature on animal ethics and animal welfare has given scarce consideration to how tourists become enrolled into caring, responsible practices towards animals. The objective of this paper is to contextualize a process of moral development – and specifically the emergence of an ethic of care – through the narratives and experiences of captive elephant volunteer tourists in Thailand. Guided by tenets of ecofeminism and a narrative methodology, our study forefronts how relational experiences prompted compassion and empathy as storied by 12 women volunteers. These volunteer tourists described how they shaped their own moral and ethical patterns through practices of witnessing abuse, questioning moral responsibilities, connecting with elephants, and advocating for improved conditions of captive individuals. As storied by the volunteers, processes of witnessing–questioning–connecting–advocating were deeply transformational, and inspired what we interpret as the development of an ethic of care. The research advances understandings of how intentional, relational engagements that prioritize animal wellbeing have the potential to facilitate among tourists processes of becoming care-full.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".