The EI family supplement and relative income in two-earner families with children
Bibliographic record
Abstract
The purpose of the present report is to contribute to a better understanding of how women and men are adjusting to changes in benefit levels as a result of the Employment Insurance (EI) Act. Specifically, we investigate the relative incomes of wives and husbands, paying particular attention to couples with children. The main focus of attention here is the EI Family Supplement (FS), with special reference to two-earner families with children. Early administrative data indicate that the FS has provided a substantially higher income top-up to eligible individuals. However, a gender impact analysis should also take into account the situations of ineligible individuals, as well as those of eligible individuals. It is at the line between eligibility and ineligibility that the issues addressed in the present report arise. The report uses 1997 data from the Canadian Out of Employment Panel (COEP) Survey, together with administrative data from Human Resources Development Canada’s (HRDC) employment insurance files, to analyze the situations of husbands and wives in families where there has been an employment separation. The empirical foundation is a National Database of 26,384 survey respondents, which was produced by integrating data from seven COEP cohorts that were all interviewed at some time during 1997. From this sample, a subsample of individuals in couples was selected. The subsample, which is the basis for the analysis in this report, consists of 12,773 persons who experienced a job separation and who had a co-resident spouse at the time of interview in a household that did not contain any other adults. In order to examine potential implications of the EI program for families, the principal factors analyzed are as follows: EI benefits filtering, FS filtering, relative income, financial dependence and economic stress. The report contains 17 tables.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".