Study on Work, Attitudes Concerning Soscial Benefits, Pensions and Unemployment, 1984
Bibliographic record
Abstract
Many of the projects in the social science research field that have been funded by the Research Council collect data from sample investigations. In order to coordinate and utilize technical and financial resources in a better way, NAVF's coordination committee for interviews was created in January of 1983. The committee would we responsible for conducting surveys in which researchers and scientists could apply to take part in a shared program. In 1984 the committee decided to perform a pilot project with Statistics Norway. Five projects from difference research groups participated with questions in a supplementary survey for Statistics Norway's Labour Force Survey (AKU) 3rd quarter 1984. The purpose of this was to test the possibility of creating a Norwegian General Social Survey, an omnibus survey for research purposes. The intention was to provide data concerning various aspects of the population's employment, occupational mobility and the family provider's profession. Another goal was to illustrate how different groups view different occupations in situations such as recommending them to young persons, the occupation's reputation and social influence. The project also included a section regarding opinions on using social benefits, national insurance and the fear of unemployment.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".