Family Welfare Effort, Total Fertility, and In Vitro Fertilization: Explaining the Israeli Anomaly
Bibliographic record
Abstract
The theory of family welfare effort is a leading macro-sociological explanation of variation in human fertility. It holds that states which provide universally available, inexpensive, high-quality day care, generous parental leave, and flexible work schedules lower the opportunity cost of motherhood. They thus enable women, especially those in lower socioeconomic strata, to have the number of babies they want. A considerable body of research supports this theory. However, it is based almost exclusively on analyses of Western European and North American countries. This paper examines the Israeli case because Israel's total fertility rate is anomalously high given its family welfare effort. Based on a review of the relevant literature and a reanalysis of data from various published sources, it explains the country's unusually high total fertility rate as the product of (1) religious and nationalistic sentiment that is heightened by the Jewish population's perception of a demographic threat in the form of a burgeoning Palestinian population and (2) the state's resulting support for pro-natal policies, including the world's most extensive in vitro fertilization (IVF) system. The paper also suggests that Israel's IVF policy may not be in harmony with the interests of many women insofar as even women with an extremely low likelihood of becoming pregnant are encouraged to undergo the often lengthy, emotionally and physically painful, and risky process of IVF.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| 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".