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Record W2148346951 · doi:10.1111/1477-8947.12035

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

2014· article· en· W2148346951 on OpenAlex
Julie Babinard, Christopher R. Bennett, Marea Eleni Hatziolos, Asif Faiz, Anil Somani

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNatural Resources Forum · 2014
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsEsri (Canada)
Fundersnot available
KeywordsSustainabilityContext (archaeology)ReefAtollNatural resourceThreatened speciesBusinessEnvironmental resource managementEnvironmental planningFisheryGeographyEnvironmental scienceEcologyHabitat

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.197
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it