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Record W6925680985 · doi:10.18712/nsd-nsd1303-v1

Granted and declined applications for disability pension

2009· dataset· en· W6925680985 on OpenAlexaboutno aff

Bibliographic record

VenueNSD – Norsk senter for forskningsdata · 2009
Typedataset
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSocial securityDisability insuranceQuarter (Canadian coin)Disability pensionPensionWork (physics)Social insurancePoint (geometry)Population

Abstract

fetched live from OpenAlex

The project builds upon the work that was done in connection with the public report of the national insurance disability term (NOU 1977:14). This project has repeated surveys that were carried through in the period 1975-80 on the basis of the new view of alcoholism as equal with other illnesses. The report group gave an overview of the population on social security that built upon the national insurance register. Also, it was produced an overview of those who had their application for social security turned down and it was carried through a survey at three counties in the fourth quarter of 1975 in order to clarify how the percentage of granted applications vary between various diagnosis groups. As a fourth point in the rapport it was carried through a survey at 18 social security offices in order to get an overview of how many of the social welfare clients would be potential disability pensioners by changing or disbanding the medical conditions for right to disability pension.

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)0.002
metaresearch head score (Gemma)0.009
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.038
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0280.022

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 head0.024
GPT teacher head0.270
Teacher spread0.246 · 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
GenreDataset

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
Published2009
Admission routes1
Has abstractyes

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