The <scp>QATSDD</scp> critical appraisal tool: comments and critiques
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: The aim of this research note is to reflect on the effectiveness of the QATSDD tool for its intended use in critical appraisals of synthesis work such as integrative reviews. METHODS: A seven-member research team undertook a critical appraisal of qualitative and quantitative studies using the QATSDD. RESULTS AND CONCLUSION: We believe that the tool can spur useful dialogue among researchers and increase in-depth understanding of reviewed papers, including the strengths and limitations of the literature. To increase the clarity of the process, we suggest further definition of the language in each indicator and inclusion of explicit examples for each criterion. We would also like to see the authors outline clear parameters around the use of the tool, essentially stating that the tool should be used in synthesis work for studies of mixed methods or work that includes qualitative and quantitative research informed by a positivist paradigm. In the context of an appropriate team composition, the tool can be a useful mechanism for guiding people who are coming together to discuss the merits of studies across multiple methodologies and disciplines.
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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 | 0.292 | 0.779 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.016 | 0.017 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.017 | 0.026 |
| Insufficient payload (model declined to judge) | 0.020 | 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".