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Record W4380575458 · doi:10.1017/9781009184175.002

Introduction

2023· book-chapter· eo· W4380575458 on OpenAlexaff
Megan Bradley, Cathryn Costello, Angela Sherwood

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook-chapter
Languageeo
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This introductory chapter sets the stage for the contribution advanced in this volume. First, it provides a brief overview of IOM’s history and structure. Second, it offers a primer on IOM’s entry into the UN system as a related organization in 2016. Third, it situates the book in relation to the core concepts underpinning it, including the obligations, accountability, and expansion dynamics of international organizations (IOs). Fourth, it draws out key themes running through the volume, particularly in relation to grounding assessments of IOM in international law; understanding IOM’s roles as a norm ‘breaker, taker and shaper’; analysing IOM as a protection actor; and developing more complex accounts of institutional change at IOM. Fifth, it maps out the structure, scope and limitations of book. Finally, it reflects on the legal and political implications of this volume, focusing on the need to recast the IOM Constitution to centre not only the organization’s obligations to its member states but also to the migrants it claims to serve.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.031
GPT teacher head0.228
Teacher spread0.197 · 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 teacher head, not a consensus.

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

Citations15
Published2023
Admission routes1
Has abstractyes

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