A new village in Sri Lanka: learning lessons there, sharing lessons here
Bibliographic record
Abstract
Purpose The authors have three purposes in writing this paper: to share the authors' experiences “catalyzing” reconstruction of a village in southern Sri Lanka four months after its destruction by the Indian Ocean tsunami, to suggest that what the authors learned in a “developing world” setting has relevance in the authors' “developed world” classrooms and practices, and to consider the tactics that locals took both to engage and resist the authors' assistance. Design/methodology/approach The authors' approach was participatory (working as laborers for ten days), reflective (reconsidering the authors' experiences two years later and finding their influence in the authors' recent work with students), and theoretical (layering an autoethnographic framework over the authors' reflections). Findings It is found that traces of the Sri Lankan project can be found in the authors' work with students in the USA and Canada, and that while it is possible to find examples of locals' resistance within the village rebuilding process, incorporating such potentials and perspectives into the authors' everyday work as professors has its own complexities. Originality/value It is the authors' hope that this case study will contribute to the reversal of a dominant Western and educated perspective that “we” know what is best for “them” and that “they” must learn to appreciate what “we” have in mind. This challenge is taken by highlighting applications “here” of the authors' lessons learned “there” and by making themselves aware of how locals of all sorts and locations often resist the intentions of others, no matter how considered and shared the plans might be.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".