PROTOCOL: Searching and reporting in Campbell Collaboration systematic reviews: An assessment of current methods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.623 | 0.443 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.026 | 0.002 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it