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Record W2553771344 · doi:10.1002/job.2163

Analyzing if and how international organizations contribute to the sustainable development goals: Combining power and behavior

2016· article· en· W2553771344 on OpenAlex
Ben Cormier

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Organizational Behavior · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsSmiths Detection (Canada)University of Toronto
Fundersnot available
KeywordsBureaucracyScholarshipAutonomyPower (physics)PoliticsInternational relationsSustainable developmentPolitical scienceCore (optical fiber)Public relationsComputer scienceLaw

Abstract

fetched live from OpenAlex

Summary Can International Organizations (IOs) such as the World Bank, United Nations, and International Labor Organization contribute to the Sustainable Development Goals (SDGs)? This article argues that this is best analyzed by simultaneously considering two sets of factors: the international political constraints external to IOs and the organizational processes and structures internal to IOs. More specifically, this article suggests that such analyses can take place by combining scholarship on International Relations (IR) and Organizational Behavior (OB). The article defines international power, outlines various constraints on IO autonomy, and suggests that OB and IR are well positioned to jointly improve the study of IO employment practices, organizational structures, bureaucratic politics, and inter‐organizational effects. The core aim is to provide justification and material for combining IR and OB in further research on IOs.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.272
Teacher spread0.263 · 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