WAGES in CANADA: SCF, SLID, LFS and the Skill Premium
Bibliographic record
Abstract
For the years 1981 to 1997 the Survey of Consumer Finances served as the main source of information about the earnings of individuals, households and families. The Survey of Labour Income Dynamics, begun in 1993, was intended to replace and to improve upon the SCF. The Labour Force Survey which began releasing earnings information in 1997 (the last year of the SCF) is a second alternative for extending historical earnings data to the present day. This paper examines the extent to which either of these two surveys can be used to extend the SCF series to more recent times. Neither survey comes off as satisfactory in all respects as an extension of SCF earnings data though if one's purposes are more limited, such as studying the education premium, then merging results from the SCF and SLID seems a reasonable way to proceed. It is not possible here to assess the ability of SLID or LFS to extend the SCF for other applications. But this method could easily be adapted to address other similar questions.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.018 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".