Post-Tsunami recovery : issues and challenges in Sri Lanka
Bibliographic record
Abstract
This is one of the first analytical reports on the major lessons learned from Sri Lanka’s experience of the tsunami and the response in the rebuilding phase: Promised external assistance appeared at first to be more than adequate to cover reconstruction costs in full. But problems soon emerged with relief payments, providing credit facilities, distribution of funds, coordination of reconstruction activities, and mismanagement of funds. Progress has been slow, uneven, and concentrated in certain areas, while missing other regions. Poor coordination among domestic and external agencies has emerged as a serious problem, together with the sensitive issue of balancing political considerations and humanitarian assistance to the needy. Some international NGOs’ reluctance to cooperate with government institutions, and competitive behavior towards other agencies have hampered coordination and implementation. The modalities of aid spending, including procedures and mechanisms need to be reviewed to improve quick and effective responses. Problems with aid utilization and accountability must be urgently addressed. Practical policy recommendations made in this report include: livelihood related cash payments to households; assistance for rebuilding houses; titles to new houses; buffer zone rules; early warning and disaster management systems; coordination of donor assisted activities and macroeconomic policy issues. Doubtless other tsunami-affected countries could benefit from a similar study by local scholars to reconfirm applicable lessons and to identify home-grown solutions so that something of lasting positive value may yet come out of this appalling tragedy.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".