Chitwan Valley Family Study: Changing Social Contexts and Family Formation, Nepal, 1995-2019
Bibliographic record
Abstract
The study was designed to investigate the influence of changing social contexts on family formation behaviors, marriage, childbearing, and contraceptive use. The research investigates the extent to which changes in the community produce changes in family formation behavior, and whether the family organization of individual life courses produces these changes in behavior. The study used a combination of ethnographic and survey research methods to gather 171 neighborhood histories, 142 school histories, 118 health service histories, 20 bus route histories, household farming practices, family planning histories, and household composition in Western Chitwan, Nepal. Personal histories were gathered from the 5,271 individuals ages 15-59 years living in these neighborhoods using a semi-structured Life History Calendar and a highly structured survey questionnaire. The sample neighborhoods for this study were chosen to represent the five major ethnic groups inhabiting the area: high caste Hindus, hill Tibeto-Burmese (such as Gurung, Tamang, and Magar), indigenous terai Tibeto-Burmese (such as Tharu, Darai, and Kumal), Newar, and other caste Hindus. Neighborhood history calendars measured the neighborhood's distance, in terms of minutes walking, to a variety of organizations and services. Schools were defined as places of instruction for children of any age or grade. Health clinics were defined as any places of care and healing, such as doctors' offices, hospitals, and health posts. Employers were any places that employed 10 or more people for pay. Cinemas were movie theaters or halls where movies were shown. Bus stops were any places where people could obtain a ride for pay on a vehicle. This particular study spanned 1995-2017. These data were combined with data from the Chitwan Valley Family Study 1996-1997, and the Household Agriculture and Consumption Survey 1996. ** IMPORTANT NOTE FOR STATA USERS ** The Stata files for datasets 7, 15, 16, 18, and 32 were produced in Stata 13. Users of earlier versions of Stata will not be able to read them. There are a few options for users of Stata 12 or earlier to work around the compatibility issue: - Upgrade to Stata 13 - Find a computer with Stata 13 and use the 'saveold' command to create a Version 12 file - Use the latest version of a file conversion utility, such as Stat/Transfer (older versions cannot read Stata 13 files)
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".