The Prediction of Labor Force Status: Implications From International Adult Skill Assessments
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This report investigates the prediction of labor force status using observed variables, such as gender, age, and immigrant status, and more importantly, measured skill variables, including literacy proficiency and a categorical rating of educational attainment based on the 1994 International Adult Literacy Survey ( IALS ), the 2003 Adult Literacy and Life Skills Survey ( ALL ), and the 2011 Programme for the International Assessment of Adult Competencies ( PIAAC ) projects. We explored the regression relations in the past two decades for six trend countries and subnational regions that provide data for all assessments: the United States, Norway, the Netherlands, Italy, Canada's English‐speaking region, and Canada's French‐speaking region. Probit regression models with latent predictors were used in this cross‐sectional study to investigate how those variables are structurally related to labor market outcomes. Results show the importance of literacy proficiency and education in determining individuals' labor force status across countries/regions, but with key differences among these countries/regions.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it