PROTOCOL: Searching and reporting in Campbell Collaboration systematic reviews: An assessment of current methods
Bibliographic record
Abstract
This is the protocol for a Campbell review. The aim of this study is to comprehensively assess the quality and nature of the search methods and reporting across Campbell systematic reviews. The search methods used in systematic reviews provide the foundation for establishing the body of literature from which conclusions are drawn and recommendations made. Searches should be comprehensive and reporting of search methods should be transparent and reproducible. Campbell Collaboration systematic reviews strive to adhere to the best methodological guidance available for this type of searching. The current work aims to provide a comprehensive assessment of the quality of the search methods and reporting in Campbell Collaboration systematic reviews. Our specific objectives include the following: To examine how searches are currently conducted in Campbell systematic reviews. To identify any machine learning or automation methods used, or emerging and less commonly used approaches to web searching. To examine how search strategies, search methods and search reporting adhere to the Methodological Expectations of Campbell Collaboration Intervention Reviews (MECCIR) and PRISMA guidelines. The findings will be used to identify opportunities for advancing current practices in Campbell reviews through updated guidance, peer review processes and author training and support.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Reporting · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Metaresearch Domain: Methods · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.447 | 0.667 |
| Meta-epidemiology (narrow) | 0.006 | 0.010 |
| Meta-epidemiology (broad) | 0.014 | 0.018 |
| Bibliometrics | 0.027 | 0.032 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.008 | 0.013 |
| Research integrity | 0.014 | 0.023 |
| Insufficient payload (model declined to judge) | 0.144 | 0.049 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".