Evaluation of the Task Assessment and Planning (TAP) Project in Five Provinces of Cambodia
Bibliographic record
Abstract
The evaluation explains the context of the TAP project in Cambodia, the task assessment and planning projects, methods and measures, as well as results. The study also provides as summary assessment, discusses lessons learned and lists recommendations. The Task Assessment and Planning (TAP) Project has come at a critical juncture for mine action in Cambodia. It is a time when a few donors, Canada among them, argue strongly that mine action is best served by building capacity among provincial government groups for setting mine action priorities. Few donors would take exception to this in principle, but in practice the more influential ones continue to provide support to clearance operators – HALO Trust and MAG – whose policies are less committed to building government capacity. The TAP project was expected to make the case for the perspective Canada endorses: that with coaching, skills and equipment, provincial mine action planning bodies can make informed decisions in the best interest of all.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".