Survey of Consumer Finances, 1987 [Canada]: Key File
Bibliographic record
Abstract
The Survey of Consumer Finances (SCF) is conducted annually to obtain work experience and income information from Canadian households. The Survey provides up-to-date information on the distribution and sources of income, before and after taxes, for families and individuals. With this file, users may identify specific family types, such as two-parent and lone-parent families. Information is also provided on earnings, transfers, and total income for the head and the spouse of the census family unit, as well as personal and labour-related characteristics. This reference year for this file is 1986. Commencing with the 1998 microdata files, annual cross-sectional income data will be sourced from the Survey of Labour and Income Dynamics (SLID). The purpose of this file is to enable users to combine the other Survey of Consumer Finances and Household Income, Facilities and Equipment files into custom-tailored household and sub-household units. This file consists of one record for each child and adult in the surveys' samples. Each key file record has the identification numbers for the correponding household, economic family, census family, and individual. Each record has the household (HH), economic family (EF), census family (CF), and the individual 15+ microdata tape identification numbers of the individual.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.025 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.056 | 0.022 |
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".