MétaCan
Menu
Back to cohort
Record W2336963216

SOEP 2012 - Codebook for the $PEQUIV file 1984-2012. CNEF variables with extended income information for the SOEP

2013· article· en· W2336963216 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEconstor (Econstor) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsnot available
FundersCollege of Veterinary Medicine, Cornell UniversityKorea Labor Institute
KeywordsCodebookComputer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

The $PEQUV-File is based on the Cross-National Equivalent File (CNEF) with extended income information for the SOEP. This file comprises not only the aggregated income figures provided in the CNEF but also further single income components. The CNEF is a joint effort of researchers and staff affiliated with Cornell University, the DIW Berlin, the University of Essex, Statistics Canada, the Melbourne Institute of Applied Economics and Social Research (MI), the Korea Labor Institute and the Swiss Foundation for research in Social Sciences (FORS) funded by the National Institute on Aging and by the DIW Berlin. For extensive documentation of the CNEF cf. http://www.human.cornell.edu/che/PAM/Research/Centers-Programs/German-Panel/cnef.cfm or: Joachim R. Frick, Stephen P. Jenkins, Dean R. Lillard, Oliver Lipps, and Mark Wooden (2007): The Cross-National Equivalent File (CNEF) and its Member Country Household Panel Studies. In: Schmollers Jahrbuch (Journal of Applied Social Science Studies), 127(4) , p. 627-654.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.488
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.018
GPT teacher head0.258
Teacher spread0.241 · 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