MétaCan
Menu
Back to cohort
Record W4353027924 · doi:10.1093/sf/soad020

World Society Corridors: Partnership Patterns in the Spread of Human Rights

2023· article· en· W4353027924 on OpenAlexaff
Ioana Sendroiu, Ron Levi

Bibliographic record

VenueSocial Forces · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Comparative Analysis Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHuman rightsNormativeGeneral partnershipSociologyPolitical scienceProcess (computing)Law and economicsEpistemologyLawComputer science

Abstract

fetched live from OpenAlex

Abstract Considerable sociological work shows that the human rights regime is rapidly expanding through isomorphic processes. We provide new insight into human rights diffusion through an analysis of the Universal Periodic Review (UPR), a global forum in which all states receive human rights recommendations from their peers. We convert the roughly 50,000 recommendations from the first two cycles of the UPR into a relational dataset of states making and receiving recommendations, inductively modeling this process of human rights diffusion through latent class regression. Building on research in the new institutionalism, we find that asymmetric relationships between states make it less likely for human rights recommendations to be accepted, with accepted recommendations tending to be more general and easier to implement. We argue that these partnership patterns provide evidence for normative corridors that give world society its shape. By drawing together world society approaches with relational sociology, we develop new insights into the structuration of human rights and normative change more broadly.

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)0.007
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0010.003
Scholarly communication0.0050.006
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.230
GPT teacher head0.508
Teacher spread0.278 · 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 designQualitative
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

Citations13
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueSocial ForcesSame topicQualitative Comparative Analysis ResearchFrench-language works237,207