Bibliographic record
Abstract
The most familiar form of group interview is called focus group discussion (FGD). The use of FGD is widespread. This method derives from market research strategies but now come into common use in social science research area. The FGD can in the best of circumstances, bring out a lot of general information if it is perfectly performed. It is much needed to understand the roles of all members of the team in the field. This article is an attempt to discuss and analyze the roles of FGD team members. Key word: FGD; research method; team work; responsibility; quality information.Resume: La forme la plus courante de l'entrevue de groupe est appelee le groupe de discussion. L'utilisation de groupe de discussion est tres repandue. Cette methode est derivee des strategies de recherches de marche, mais maintenant elle est de l'usage commun dans le domaine de recherches des sciences sociales. Dans le meilleur des cas, le groupe de discussion peut faire ressortir beaucoup d'information generale si elle est parfaitement realisee. Il est indispensable de comprendre les roles de tous les membres du groupe sur le terrain. Cet article est une tentative de discuter et d'analyser les roles des membres de groupe de discussion.Mots-cles: groupe de discussion; methode de recherches; travail en equipe; responsabilite; information de qualite
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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 | 0.030 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".