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Record W210594973 · doi:10.5070/p8301022241

Migration for Environmentally Displaced Pacific Peoples: Legal Options in the Pacific Rim

2012· article· en· W210594973 on OpenAlexaboutno aff
Gil Marvel Tabucanon

Bibliographic record

VenueUCLA Pacific Basin Law Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationLegislationPacific RimDiscretionPolitical scienceSmall Island Developing StatesEnvironmental lawDevelopment economicsInternational tradeEconomic growthClimate changeBusinessLawEconomicsGeography

Abstract

fetched live from OpenAlex

This paper explores the complex relationship between the environment and migration, namely the various protection options available for environmentally-displaced Pacific peoples under the laws of the United States, Canada, Australia, and New Zealand. It seeks to ascertain whether flexibility exists in these countries' domestic laws for environmental migrants from neighboring Pacific countries. It asks if humanitarian and ministerial discretion admissions and preferential admission schemes sufficiently address potential Pacific island relocations brought about by global warming and climate change, and identifies both opportunities and challenges in legislation. This paper argues that in the absence of an international legal protection regime for environmental migrants, states need to expand immigration opportunites for persons fleeing from environmental threats. In recent decades, the four above-mentioned Pacific Rim states have developed relatively open and liberal migration policies, albeit not specifically geared towards environmental migration. Admitting environmental migrants under equitable and just terms is not only in line with the fundamental values and interests of these Pacific Rim states, but it is also central to their ethical, humanitarian, and domestic legal obligations, although the latter are ad hoc and limited.

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)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.105
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.016
Scholarly communication0.0050.004
Open science0.0020.007
Research integrity0.0040.005
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 head0.057
GPT teacher head0.299
Teacher spread0.242 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2012
Admission routes1
Has abstractyes

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