Investigating the causal relationship between employment and informal caregiving of the elderly
Bibliographic record
Abstract
OBJECTIVE: Examining the causal relationship between employment and informal caring to date has been impeded in countries like Ireland where there is a lack of suitable panel data and/or variables for instrument construction. This paper employs propensity score matching to control for non-random selection into treatment and control groups which controls for differences in employment outcomes between carers and non-carers in Ireland using data from Quarterly National Household Survey 2009 Quarter 3. Earlier papers focus on using regression techniques which may lead to biased estimates. RESULTS: Results suggest that differences exist between carers and non-carers with respect to their employment status in Ireland. Overall the results suggest that the effects are more significant for those providing greater hours of informal care per week than those providing fewer hours of care per week. The effects estimated in this paper are likely to be more precise as failing to account for potential biases in the relationship are likely to underestimate the true effect of caring on employment outcomes. We find that propensity score matching provides an alternative method of examining the relationship when suitable panel data and/or variables for instrument construction are not available.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".