Scientists' collaboration in the social sciences field: Investigating the determinants of scholarly collaboration in the Canadian context 2001–2008
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
In the era of knowledge-based economies, knowledge production and transfer have emerged as a crucial component of innovation and human capital development. Science activities are globalizing and research partnerships will become increasingly imperative. Hence a considerable trend in research collaboration has been noted in the literature. Over the last few years, collaboration among scientists has been on the rise [1] and the different ways in which this collaboration takes place have been the subject of many conceptual [2] and empirical studies [3]. Furthermore, the analysis of the relationship between research inputs (grants, infrastructure spending, training of researchers, etc.) and research outputs (collaboration, productivity, citation, impact, etc.) has also been the subject of several explanatory studies, mostly done in OECD countries, whether in France [4], the United States [5], Italy [6], New Zealand [7], the United Kingdom [8], Australia [14], or the European Union [9].
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 | 0.021 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.049 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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