MétaCan
Menu
Back to cohort
Record W2289583826 · doi:10.1787/5jm3npvrl832-en

Economic Theory and Practical Lessons for Measuring Equality of Opportunities

2016· paratext· en· W2289583826 on OpenAlex

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

VenueOECD statistics working papers · 2016
Typeparatext
Languageen
FieldSocial Sciences
TopicIncome, Poverty, and Inequality
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceMathematical economicsEconomics

Abstract

fetched live from OpenAlex

The High-Level Expert Group on the Measurement of Economic Performance and Social Progress (HLEG), hosted by the OECD, has been established to follow-up on the recommendations of the Commission on the Measurement of Economic Performance and Social Progress (also known as the Stiglitz-Sen-Fitoussi Commission) and to provide impetus and guidance to the various initiatives currently ongoing on measuring people's well-being and societies' progress. The work of the HLEG provides leadership on measuring well-being and progress worldwide and informs the OECD's own work on measuring well-being and progress. This working paper draws on a presentation made in the context of a thematic workshop organised by the HLEG. For more information, visit: www.oecd.org/statistics/measuring-

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.214
GPT teacher head0.406
Teacher spread0.192 · 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