International Ties at Peripheral Sites: Co-producing Social Processes and Scientific Knowledge in Latin America
Bibliographic record
Abstract
In recent decades, scientific knowledge has been increasingly expected to contribute to the resolution of public and controversial issues in Latin America. However, in peripheral sites of knowledge and economic production, the dynamics of both science and society have been complicated by tensions between the demands of local stakeholders and the ties with the global centers of technical and scientific expertise. First, local public issues are often addressed in merely discursive ways, rather than effectively, in research and expert advice; second, local scientific elites often establish links with experts and the global centers of science in order to legitimate their stance against competing approaches. An analysis of four case studies (neglected diseases, mining pollution, wildlife conservation and migration studies) involving the production of scientific knowledge intended to address public issues in Latin America reveals, first, that material and symbolic asymmetries determine the outcomes of these engagements and, second, that international ties with peripheral sites affect the cognitive definition of the issues at stake and the range of public interventions devised to address them. Yet, in these four case studies, the key actors that mediate links between local stakeholders and international counterparts – or, ‘drivers’ – mobilize the bodies of knowledge that, ultimately, shape the cognitive and political contours of the social issues at stake.
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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.013 | 0.029 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.001 | 0.021 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".