CHLA 2023 Conference Lightning Talks/Congrès de l'ABSC 2023: Présentations Éclair
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
Introduction: There are numerous benefits for researchers to involve a librarian in their knowledge synthesis projects such as better search precision and higher quality search strategy and methodological reporting.However, does librarian involvement make a difference when it comes to publication venue?This research examines if any correlation exists between librarian involvement on published knowledge syntheses, and the impact factor of the journals where they are published.Methods: Focusing on the journals from a single category ('Psychology, Clinical') in Clarivate's Journal Citation Reports (JCR), the authors analyzed the librarian involvement (co-author, acknowledged, unclear or none) in a complete set of English language knowledge syntheses published over a one-year period (2020).Results: Librarians were co-authors on 2.7%, and acknowledged in 11.7% of the 551 knowledge syntheses examined.Dividing the included documents into similar sized groups, we defined four impact factor ranges: G1=12.792 to 7.169; G2=6.724 to 4.507; G3=4.473 to 3.368; G4=3.311 to 0.342.The proportion of knowledge syntheses with librarian co-authors and librarian acknowledgements were, respectively; G1: 3% and 11.1%; G2: 2.1% and 7.7%; G3: 5.1% and 16.7%; and G4: 0.7% and 11.9%.Discussion: Although G3 showed higher percentages of librarian co-authorship and acknowledgment than the other groups, the number of librarian co-authored papers in the document set was too low for chi-squared significance testing.Further research in a JCR category with a higher proportion of librarian co-
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.
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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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