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Standard Setting and International Peer Review

2019· reference-entry· en· W2961396973 on OpenAlexaff
Leslie A. Pal

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsCarleton University
Fundersnot available
KeywordsSketchVariety (cybernetics)TreatyPolitical sciencePublic relationsKey (lock)Knowledge managementBusinessComputer scienceLawComputer security

Abstract

fetched live from OpenAlex

The OECD, established in 1961 and now consisting of thirty-six member states, has unique features as an intergovernmental and transnational actor because it is neither a lending nor a treaty organization. It relies primarily on knowledge production, standard-setting, and monitoring techniques, such as comparative data, and most prominently, peer review. The chapter begins with a sketch of the organization’s highly intricate structure of committees, centres, boards, forums, working groups, and networks (over 250 such specialized bodies), and the supporting secretariat of directorates. Complementing this complex internal structure is an equally complex array of global engagements with other international actors through partnerships, forums, and networks. The OECD’s influence arises from its unmatched capacity to produce credible knowledge, define key policy concepts, and promote standards (through a variety of different types of international decisions, conventions, and recommendations). Its signature compliance and monitoring technique is peer review.

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)0.138
metaresearch head score (Gemma)0.276
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.138
Threshold uncertainty score0.731

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1380.276
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0090.007
Science and technology studies0.0090.016
Scholarly communication0.0230.012
Open science0.0050.010
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0170.012

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 head0.034
GPT teacher head0.283
Teacher spread0.249 · 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 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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