Bibliographic record
Abstract
Qualitative synthesis within the family of systematic reviews meets an urgent need to use knowledge derived from qualitative studies to inform practice, research, and policy. Despite the contingent nature of evidence gleaned from the synthesis of qualitative studies, systematic synthesis is an important technique and, used judiciously, can deepen our understanding of the contextual dimensions that emerge from qualitative research. This book presents an overview for planning, developing, and implementing qualitative synthesis within existing protocols and guidelines for conducting systematic reviews. The book also explores methodological challenges, including: the philosophical tensions of integrating qualitative synthesis within the family of systematic reviews; the balance of comprehensive and iterative information retrieval strategies to locate and screen qualitative research; the use of appraisal tools to assess quality of qualitative studies; the various approaches to synthesize qualitative studies, including interpretive, integrated, and aggregative; and the tensions between the generalizability and transferability of findings that emerge from qualitative synthesis.
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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 | 0.235 | 0.413 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.023 | 0.024 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.044 | 0.013 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".