Academic dependency: the influence of the prevailing international biomedical research agenda on Argentina’s CONICET
Bibliographic record
Abstract
Background: The prevailing health and biomedical sciences (HBMS) research agenda, not only determined by leading academic institutions but also by large pharmaceutical companies, has been shown to prioritize the exploration of novel pharmacological interventions over the study of the socio-environmental factors influencing illness onset and progression. The aim of this investigation is to quantitatively explore whether and to what extent the prevailing international HBMS research agenda and the key actors setting this agenda influence research in non-core countries. Methods: We used the Web of Science database and the CorText platform to proxy the HBMS research agenda of a prestigious research institution from Latin America: Argentina's National Research Council (CONICET). We conducted a bibliometric and lexical analysis of 16,309 HBMS academic articles whereby CONICET was among the authors' affiliations. The content of CONICET's agenda was represented through co-occurrence network maps of the most frequent concatenation of terms found in titles, keywords, and abstracts. We compared our findings with previous reports on the international HBMS research agenda. Results: In line with the results previously reported for the prevailing international agenda, we found that terms linked to molecular biology and cancer research hegemonize CONICET's HBMS research agenda, whereas terms connecting HBMS research with socio-environmental cues are marginal. However, we also found differences with the international agenda: CONICET's HBMS agenda shows a marginal presence of terms linked to translational medicine, while terms associated with categories such as pathogens, plant research, agrobiotechnology, and food industry are more represented than in the prevailing agenda. Conclusions: CONICET's HBMS research agenda shares topics, priorities, and methodologies with the prevailing HBMS international research agenda. However, CONICET's HBMS research agenda is internally heterogeneous, appearing to be mostly driven by a combination of elements that not only reflect academic dependency (the adoption of the prevailing research agenda by non-core research institutions) but also local economic determinants associated with Argentina's place in the international division of labor as an exporter of primary goods.
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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 | 0.024 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.020 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".