Introduction du générateur de liens sociaux par contextes (GLSC) dans une approche mixte : Etude sur l’hétérogénéité dans les liens de collaboration des chercheurs en biotechnologie et en sciences de la vie
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 to the Social Context Name Generator (GLSC) in a Mixed Methods Approach — Study of the Heterogeneity of Researcher Cooperation Links in Biotechnology and Life Sciences: Are social dynamics in the field of biotechnology research more heterogeneous than those of other fields? To answer this question, we have constructed a tool producing comparable data on collaboration networks in three practice settings. The Contextual Social Ties Generator (CSTG) was administered in the fall of 2009 to 735 Quebec researchers from three sectors: health sciences, natural sciences, and engineering. Results indicate that the morphology of social networks significantly differs in the context of funding for a majority of researchers, regardless of their discipline. Results also counter the hypothesis according to which collaboration practices are significantly more heterogeneous in university biotechnology and life sciences research.
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 | 0.053 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 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