The Effect of Same-Sex Marriage Laws on Different-Sex Marriage: Evidence From the Netherlands
Bibliographic record
Abstract
It has long been argued that the legalization of same-sex marriage would have a negative impact on marriage. In this article, I examine how different-sex marriage in the Netherlands was affected by the enactment of two laws: a 1998 law that provided all couples with an institution almost identical to marriage (a "registered partnership") and a 2001 law that legalized same-sex marriage for the first time in the world. I first construct a synthetic control for the Netherlands using OECD data for the period 1988-2005 and find that neither law had significant effects on either the overall or different-sex marriage rate. I next construct a unique individual-level data set covering the period 1995-2005 by combining the Dutch Labor Force Survey and official municipal records. The estimates from a discrete-time hazard model with unobserved heterogeneity for the first-marriage decision confirm the findings in the aggregate analysis. The effects of the two laws are heterogeneous, with presumably more-liberal individuals (as defined by their residence or ethnicity) marrying less after passage of both laws and potentially more-conservative individuals marrying more after passage of each law.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".