Bibliographic record
Abstract
The basic question addressed in this chapter is “Who gets what in a marriage?” I begin with the observation that any marriage involves two individuals, each of whom has their own experience of that marriage. The focus is on the economic outcomes experienced by each partner, and the influences on those outcomes. Which partner has greater control over the family’s finances? Which partner’s preferences are represented in family consumption decisions? Much of the current research on this issue, which uses family expenditure data, encounters a severe limitation: there are very few consumption items which can unambiguously be assigned to men, women or children. This paper answers the question “who gets what?” in a novel way. I use data on how families manage their finances, to find out who has access to, who manages and who controls the family finances. I also explore the determinants of financial control. Does an improvement in one spouse’s bargaining position lead to greater control over money, or is control over money simply party of the couple’s division of labor? The study is based on a new a survey of families with children in the Ottawa-Hull area carried out by the author. The paper begins with a survey of recent developments in the study of intra-household resource allocation. What do we know about how resources are allocated inside households? What do we know about why the pattern of household resources is as it is? I then go on to describe the data set used in the research, and the main empirical findings. I do not find a systematic pro-male or pro-female bias in household finances. However I do find that, as predicted by theory, partners with greater incomes have greater control over money, younger spouses do better, and there is less income pooling when one partner, especially the man, has been married before.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".