Data for: Negotiation of the Use of Medical Contraception: Levers and Obstacles within Married Couple in Benin
Bibliographic record
Abstract
Project Overview This study aims to identify the factors that influence the negotiation of the use of medical contraception within married couple in Benin. It is an integral part of a larger data collection intended to understand the high fertility in Benin through the social representations of the child, medical contraception, and abortion as well as the determinants of the negotiation of medical contraception among married people. To do this, semi-structured individual interviews were conducted in Benin in the period from February to March 2018 with 30 married people of both sexes. The analysis of these interviews made it possible to observe that the negotiation of the use of medical contraception in the married couple is influenced by incentive factors, limiting factors and a factor having an ambivalent role. The data collection was carried out in French and in local language Fon. Data Overview The shared data consist of a table listing the codes employed, their definitions, and relevant excerpts. The full transcripts cannot be shared due to participant confidentiality protections.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.071 | 0.010 |
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".