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Record W2800499818 · doi:10.1177/0011392118765214

Through a fractured gaze: The OECD, the World Bank and transnational care chains

2018· article· en· W2800499818 on OpenAlexafffund
Rianne Mahon

Bibliographic record

VenueCurrent Sociology · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsWilfrid Laurier UniversityBalsillie School of International Affairs
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBureaucracyGRASPGazeWicked problemSociologyPublic relationsBusinessPolitical scienceEconomicsComputer scienceManagementLawArtificial intelligencePolitics

Abstract

fetched live from OpenAlex

Transnational care chains can be seen as a wicked problem, i.e. one that requires coordination across a range of jurisdictions. Yet international organizations, like other bureaucracies, factor problems. While this is designed to make issues more manageable, it can also inhibit the organization’s ability to grasp, and therefore to deal adequately with, wicked problems. This article examines the way policy research conducted in different parts of the Organisation for Economic Co-operation and Development (OECD) and the World Bank manages to capture pieces of the chain but is unable to see the connections between them.

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)0.013
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: none
Teacher disagreement score0.091
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0210.070
Scholarly communication0.0210.025
Open science0.0010.014
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0050.000

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 head0.061
GPT teacher head0.420
Teacher spread0.359 · 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

Citations16
Published2018
Admission routes2
Has abstractyes

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