Exploring how sand infill is transforming Phnom Penh’s Tompun-Cheung Ek wetland
Bibliographic record
Abstract
This paper focuses on the social-ecological consequences that have emerged as sand infill has transformed Phnom Penh’s Tompun-Cheung Ek wetland. This once peri-urban wetland now hosts some of Cambodia’s biggest development projects, including gated communities and high-end shopping malls. As the wetland space has shrunk, urban farmers have struggled to grow their crops. Only one staple crop continues to be grown, morning glory ( Ipomoea aquatica ). Finding non-farming jobs in the city is proving to be difficult: youth have turned to waste picking, a practice that began during COVID-19 when schools were shut down. This case highlights Cambodia’s uneven development, directs attention to the interplay of sand and urban formation, and illustrates the loss of ecosystem services that have emerged with the filling in of the Tompun-Cheung Ek wetland.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".