Bibliographic record
Abstract
Integrating Science and Practice is published twice yearly by the Ordre des psychologues du Quebec . The goal of the journal is to provide syntheses of scientific knowledge in the area of psychology and to facilitate the transfer of scientific knowledge to the field of practice. The journal aims to give practitioners in psychology, from all areas and fields of practice, the tools they need by providing them with critical reviews of the literature and brief syntheses of knowledge on specific themes. The journal is further intended to inform the public and professionals who work in collaboration with psychologists about recent scientific and clinical developments in psy chology and about the contribution of psychologists towards improving people’s quality of life. The journal publishes articles by invitation only, following a call for proposals. Independent submissions are neither considered nor accepted. However, the editorial board may receive suggestions for themes. The choice of themes is made on the basis of their clinical relevance and their scientific, social and political relevance. Preference is given to articles that propose best practices in a specific field or context, or that question existing practices or poli cies based on available research findings. In every instance, the value of an article is assessed on the basis of its scientific merit and its potential for improving practices. All articles undergo anonymous peer review before being accepted and published.
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.
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 | 0.109 | 0.118 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.011 | 0.020 |
| Scholarly communication | 0.039 | 0.012 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.041 | 0.019 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".