Labour Force Sample Survey 1986, 3.quarter
Bibliographic record
Abstract
Statistics Norway (SSB) has conducted official quarterly Labor Force Surveys (LFS) since the first quarter of 1972. The purpose of these surveys is to provide labor market authorities and other stakeholders with insights into the occupational structure of the population and its development over time. The surveys aim to serve as a basis for labor market forecasts and research. In the LFS, respondents are interviewed in two consecutive quarters, followed by a two-quarter break, and then interviewed again in two consecutive quarters. The sample size was approximately 10,000–11,000 respondents each quarter until 1988. The 1976 Labor Force Survey represents the fifth complete annual dataset of the LFS. Initially, the LFS was intended to serve as an analytical supplement to the monthly employment statistics based on the membership records of the national social insurance offices. However, these records ceased to be used for statistical purposes when sickness benefits were integrated into the National Insurance Scheme (Folketrygden) on January 1, 1971. Over time, the LFS has evolved into the most important source of information on the labor market's status and trends. In 1975, Statistics Norway revised its sampling framework for interview-based surveys. For further details, see Article 37: *On the Use of Sampling at the Office for Interview Surveys* (Steinar Tamsfoss, SSB) and SØS 33: *Principles and Methods for Statistics Norway's Sample Surveys* (Ib Thomsen). At the same time, the estimation method for projecting national figures was modified, enabling reliable regional data from 1975 onward. This revision also altered the interview scheduling, resulting in changes to the LFS’s panel system. The 1976 Labor Force Survey introduced a slightly revised questionnaire and reverted to the original six-quarter rotation plan. The updated questionnaire improved the identification of individuals categorized as family workers and those temporarily absent from income-generating work, which led to an additional 30,000–35,000 individuals being classified as employed. The category of job seekers without income was also expanded to include individuals on involuntary temporary layoff. Questions regarding underemployment and overemployment were removed from the original questionnaire. Starting in the first quarter of 1987, the estimation method (used to project national figures) was slightly adjusted, and a minor change was made to the definition of employment. To ensure comparability over time, new versions of the LFS datasets were created retroactively to 1980. As a result, two versions of the datasets exist for the period from 1980 onward: one using the "old" estimation method and one using the "new" method. The "old" version is comparable with the originally published figures for 1972–1987, while the "new" version provides data for 1980–1987 that aligns with figures published after 1987. This file is based on the *new* estimation method.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".