MétaCan
Menu
Back to cohort
Record W2594467543 · doi:10.22329/wyaj.v33i2.4841

BUILDING INTERNATIONAL APPROACHES TO CLIMATE CHANGE, DISASTERS, AND DISPLACEMENT

2017· article· en· W2594467543 on OpenAlexfundvenueno aff
Jane McAdam

Bibliographic record

VenueWindsor Yearbook of Access to Justice · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
FundersNorges ForskningsrådUniversity of Windsor
KeywordsScope (computer science)Vulnerability (computing)Climate changeVariety (cybernetics)Context (archaeology)Disaster risk reductionHazardPsychological interventionForced migrationPolitical scienceEnvironmental planningEnvironmental resource managementGeographyComputer scienceComputer securityRefugeeLawEconomicsPsychology

Abstract

fetched live from OpenAlex

On average, one person is displaced each second by a disaster-related hazard. Most people move within their own countries, but some are forced across international borders. This article outlines the scope of existing international legal frameworks to assist people displaced in the context of disasters and climate change, and suggests a variety of different tools that are required to address the phenomenon. Legal, policy, technical and scientific interventions, including disaster risk reduction, climate change adaptation and mitigation, development, and migration opportunities, will determine whether, and for how long, people can remain in their homes, and whether doing so enables them to lead dignified lives or exposes them to risks and increased vulnerability. Identifying the need for a broad, complementary set of policy strategies necessarily affects how international law should be progressively developed in this area.

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)0.008
metaresearch head score (Gemma)0.008
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: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0090.023
Scholarly communication0.0120.017
Open science0.0020.016
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0140.001

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 head0.376
GPT teacher head0.402
Teacher spread0.026 · 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
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

Citations7
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueWindsor Yearbook of Access to JusticeSame topicClimate Change, Adaptation, MigrationFrench-language works237,207