Focus group research in family planning and reproductive health care
Bibliographic record
Abstract
Strengths and weaknesses of the focus groups method Strengths G Nobody has to speak on every issue G Responses are prompted by group members G Exposes participants to a range of opinions G Deliberation in group discussion (i.e. the more extreme first answers may be moderated) G Cost-effective compared to one-to-one interviews G Semi-structured research environment G Opportunity for follow-up and probing by facilitator and group G Helps develop theory Weaknesses G Expensive G Getting participants together/organising meeting is time consuming G Can be dominated be group members with strong personality, opinion or just 'loud' voice G Needs a skilled facilitator G Compared to conducting interviews there is less time for each individual to express ideas G Risk of ending up with conformity: minority views might not be expressed, or not be presented as strongly, as they might be in an interview
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 | 0.112 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".