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Record W2198874953 · doi:10.24043/isj.309

Water resources and the historic wells of Barbuda: tradition, heritage and hope for a sustainable future

2014· article· en· W2198874953 on OpenAlexaffvenue
Rebecca Boger, Sophia Perdikaris, Amy E. Potter, John Mussington, Reginald Murphy

Bibliographic record

VenueIsland Studies Journal · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Environmental Impact
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsSustainabilityHerdingGeographyEnvironmental planningAgricultureAnthropoceneCultural heritagePsychological resilienceAridEnvironmental resource managementNatural resource economicsPolitical scienceEnvironmental protectionEnvironmental ethicsEcologyEnvironmental scienceArchaeology

Abstract

fetched live from OpenAlex

The island of Barbuda has a relatively unique history, land tenure and geography. Unlike its Caribbean counterparts, the island is not suited to large-scale agriculture due to its arid climate and relatively thin soils. Instead, the enslaved and eventually free people of Barbuda developed a complex herding ecology centered on common land ownership. As a result, carefully designed historic wells are strategically located around the island. With the challenges brought about by climate change, an interdisciplinary, international team led by the Barbuda Research Complex is investigating the state of existing water and food resources and examining how the availability and quality of water resources have influenced local cultural practices. Barbudans and international scientists are working together to improve their resilience and live more sustainably in this new era of climatic adversity.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.221
Teacher spread0.208 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2014
Admission routes2
Has abstractyes

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