Bibliographic record
Abstract
Partnership is a term that is occurring more and more frequently in the research lexicon, an approach that is gradually becoming a sine qua non in the field of health and healthcare research in Canada. The purpose of this article is to share thoughts and experiences regarding research carried out in partnership. The relevance and necessity of partnerships in strategic health research will be examined, and the contribution of partnerships to the development and "re-centring" of intra- and interdisciplinary knowledge and knowledge transfer will be discussed. Based on the nursing and related-fields literature, the key elements of partnership, and the advantages and disadvantages of this strategy to pursuing research projects will be presented. An important issue in a professional discipline such as nursing will be discussed, i.e. the intra-disciplinary partnership between researchers and clinicians. Strategies that could enhance this particular type of partnership and avenues for catalyzing the synergy that must perforce develop, over the coming years, will be proposed.
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 | 0.222 | 0.201 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.027 | 0.082 |
| Scholarly communication | 0.049 | 0.042 |
| Open science | 0.006 | 0.056 |
| Research integrity | 0.013 | 0.019 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".