Labour Force Survey 3rd quarter 1979 - 4th quarter 1980 panel file, old estimation
Bibliographic record
Abstract
Statistics norway has conducted official quarterly labor force surveys (LFS) from Q1 1972. The survey aims to provide labor authorities and others knowledge about the occupational structure of population and development over time. The surveys provide the basis and statistical material for occupational forecasting and labor market research. In the LFS respondents are interviewed two consecutive quarters, then after two more quarters they are interviewed again in two consecutive quarters. The Labour Force Survey 1972 is the first complete LFS year long survey. Originally it was intended that such statistics would be a more analytical supplement to the monthly employment statistics based on the insurance fund membership files. The insurance fund-based statistics, however, fell away when health insurance was included in the National Insurance Scheme from 1 January 1971, the LFS has gradually evolved to become the main source of knowledge about the state of the labor market. Overview of LFS panels with detailed explanation for panel files: Group 1971 | 1972 | 1973 | 1974 | 1975 | 1976 | 1977 | 1978 | 1979 | Quarter 12345| 1234 | 1234 | 1234 | 1234 | 1234 | 1234 | 1234 | 1234 | 17 | | | | XX | XX | | | | | 18 | | | | XX | XX | | | | | 19 | | | | XX | XX | | | | | ---------------------------------------------------------------------------- 20 | | | | X | X X | X | | | | 21 | | | | | XX | XX | | | | 22 | | | | | XX | XX | | | | 23 | | | | | XX | XX | | | | ---------------------------------------------------------------------------- 24 | | | | | X | X X | X | | | 25 | | | | | | XX | XX | | | 26 | | | | | | XX | XX | | | 27 | | | | | | XX | XX | | | ---------------------------------------------------------------------------- 28 | | | | | | X | X X | X | | 29 | | | | | | | XX | XX | | 30 | | | | | | | XX | XX | | 31 | | | | | | | XX | XX | | ---------------------------------------------------------------------------- 32 | | | | | | | X | X X | X | 33 | | | | | | | | XX | XX | 34 | | | | | | | | XX | XX | 35 | | | | | | | | XX| XX| Panel files are created by linking four interviews from an ordinary interview round in LFS. In the table above this means that one could connect all the groups (lines) marked X. Group 1 is removed because the interviews started 4th quarter 1971. Participation 4 times is used as a selection criterion, therefore everyone that didn't participate in the 4th interview has been omitted. In 1975 Statistics norway changed selection strategy. The groups that were left out due to this (started in 1973 or 1974, should've had one or more interviews in 1975) are removed. This panel file covers group 35 in the table above.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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 teacher head, 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".