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Record W4404020719 · doi:10.1787/82061ed8-en

Methodology for data collection and classification

2024· book-chapter· en· W4404020719 on OpenAlexfundno aff

Bibliographic record

VenueOECD eBooks · 2024
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
FundersAlberta Biodiversity Monitoring Institute
KeywordsViet namSri lankaChinaGeographySocioeconomicsVietnameseBusinessEconomic growthEconomyEconomicsEnvironmental planning

Abstract

fetched live from OpenAlex

This report presents a comprehensive analysis of the use and structure of corporate bond markets in Asia. Based on original data, it assesses the extent to which corporations, in particular smaller growth companies, use bond markets and how that has developed over time. It also examines the regulatory frameworks that govern these markets in 19 different jurisdictions. Drawing from these findings, it formulates policy considerations for facilitating growth company access to corporate bond markets.

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)0.025
metaresearch head score (Gemma)0.060
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.138
Threshold uncertainty score0.463

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.060
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0110.013
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0040.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.1380.063

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 head0.314
GPT teacher head0.326
Teacher spread0.012 · 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
GenreMethods

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

Citations0
Published2024
Admission routes1
Has abstractyes

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