A Historical and Anthropological Comparative of the Family Planning Strategies of India and China
Bibliographic record
Abstract
The article tracks the evolution of the family planning programmes in India and China and the conceptual linkages between the two. This comparison, in turn, serves as an entry point for studying the following: The role that the family plays in becoming the site of governance and deploying state-led capitalism in the two countries. The assumptions behind the development trajectories in both countries. What are the ways in which the policies amplified patrilineal hierarchies within families to produce the disturbing outcome of the missing girl child—this even as the family planning policies became constrained as they were acting within a cultural milieu of patriarchy. The article uses studies and commentaries across disciplines, such as, historical demography and anthropology to situate its arguments. The conclusion it attempts to put forth is that the small family norm was operationalised in various differing ways in both states, and yet the commonalities that arose were the following: The declining sex ratio in both states as an immediate repercussion of the enforcement of the small family norm. The structuring of the health services around the family planning operations. The small family norm becoming an end in itself, as a mode of reaching a level of development akin to the West, and as an ethic for modernising nations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".