Sustainably managing natural resources and the need for construction materials in <scp>P</scp>acific island countries: The example of <scp>S</scp>outh <scp>T</scp>arawa, <scp>K</scp>iribati
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The growing demand for construction materials in S outh T arawa, a remote atoll in the S outh P acific, provides an example of the environmental and social challenges associated with the use of non‐renewable resources in the context of small island countries threatened by coastal erosion and climate change. In many small P acific island countries, the availability of construction materials is limited, with the majority mined from beaches and coastal reefs in an unsustainable manner. Growing demand for construction aggregates is resulting in more widespread sand mining by communities along vulnerable sections of exposed beach and reefs. This has serious consequences for coastal erosion and impacts on reef ecosystem processes, consequences that cannot be easily managed. Construction materials are also in high demand for infrastructure projects which are financed in part with support from international development agencies and donors. This paper reviews the various challenges and risks that aggregate mining poses to reefs, fish, and the coastal health of S outh T arawa and argues that the long term consequences from ad hoc beach/reef mining over large areas are likely to be far greater than the impacts associated with environmentally sustainable, organized extraction. The paper concludes with policy recommendations that are also relevant for neighbouring island countries facing similar challenges.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 it