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Record W1602041653 · doi:10.1017/cbo9780511511233.005

Human Rights INGOs and the North–South Gap: The Challenge of Normative and Empirical Learning

2006· book-chapter· en· W1602041653 on OpenAlexaff
Bonny Ibhawoh

Bibliographic record

VenueCambridge University Press eBooks · 2006
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsBrock University
Fundersnot available
KeywordsHuman rightsPolitical scienceHuman rights movementInternational human rights lawRight to propertyLinguistic rightsGlobalizationFundamental rightsEnforcementLawPublic administration

Abstract

fetched live from OpenAlex

The role of human rights International Nongovernmental Organizations (INGOs) has become increasingly important in an age of globalization in which they are seen as heralding a global civil society and a new world order based on a universal human rights. INGOs have been at the forefront of the “human rights revolution” – a revolution of norms and values that has redefined our understanding of ethics and justice. They have shaped the course of the human rights movement not only at the international level but also at regional and national levels. INGO involvements in global transnational networking, particularly in the 1980s and 1990s, have been crucial to the development of the universal human rights corpus as well as its enforcement and monitoring mechanisms. One reason for the growing influence of INGOs within the human rights movement has been their ability to build transnational coalitions and mobilize global action on key human rights issues. This is evident in the role of INGOs in such human rights milestones as the 1992 Second World Conference on Human Rights in Vienna, the establishment of a United Nations (UN) High Commission for Human Rights, and the establishment of the International Criminal Court. If the UN midwifed the postwar universal human rights movement, INGOs have weaned and nurtured it. Despite these successes, however, the work of human rights INGOs (most of which are based in the West) is increasingly underscored by operational challenges and questions over their legitimacy in the global South where they do much of their work.

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)0.011
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0050.057
Scholarly communication0.0100.026
Open science0.0020.006
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0070.001

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 head0.041
GPT teacher head0.243
Teacher spread0.203 · 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 designTheoretical or conceptual
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

Citations4
Published2006
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicHuman Rights and DevelopmentFrench-language works237,207