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Record W6944202696 · doi:10.18712/nsd-nsd0813-v1

Omnibus Study No. 2 2004

2013· dataset· en· W6944202696 on OpenAlexaboutno aff

Bibliographic record

VenueNSD – Norsk senter for forskningsdata · 2013
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Government (linguistics)TourismChristian ministryWork (physics)Information and Communications TechnologyImmigration

Abstract

fetched live from OpenAlex

Statistics Norway's Omnibus Surveys are composed of questions about various themes on behalf of several employers. The surveys consist of a fixed set of background variables, as well as the questions that employers pay for. The questions that are determined by employers can almost be considered as fixed as well, since they are used each quarter. These questions concern smoking (on behalf of the Ministry of Health Care Services) and travel over the last three months (on behalf of the Section for Transport, Tourism and ICT at SSB). Other themes that were asked about in this quarter were: - Attitudes towards immigrants (Ministry of Local Government and Regional Development) - Use of EDB in households (Division for Transport, Tourism and ICT at SSB) - Shopping abroad (Division for External Tradel at SSB) - Live-in partner statistics (Division for Social and Demographic Research at SSB) - Interest for research and technology (Norwegian Institute for Studies in Innovation, Research and Education) - Voluntary work for non-profit organization (Institute for Social Research) The Omnibus Survey in April/Mai (Omnibus nr. 2) 2004 was the second of four Omnibus Surveys in 2004.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.152
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0060.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.157

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 head0.035
GPT teacher head0.307
Teacher spread0.272 · 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; both teacher heads agree on what is shown here.

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
Published2013
Admission routes1
Has abstractyes

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Same venueNSD – Norsk senter for forskningsdataFrench-language works237,207