Bibliographic record
Abstract
The fall of the Soviet Union in 1991 heralded not only the creation and opening of borders but also the rapid entry of new actors and ideas into this previously isolated part of the world. This is typified by dramatic increases in the number of international research collaborations involving an ever-growing array of actors. Yet instead of pluralizing knowledge creation and ways of knowing, intensifying processes of globalization have given rise to a “global science” system that has not flattened or significantly altered existing knowledge hierarchies, despite greater diversity in international research collaborations. In the former Soviet state of Tajikistan, this is further tempered by resourcing gaps, political controls, and cultural factors, offering a unique setting through which to explore how researchers negotiate international research collaborations. Centering the perspectives of Tajikistani researchers, the article offers new insights into the reframing of globally homogenizing models of international research collaboration.
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 | 0.033 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.040 | 0.025 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.002 | 0.024 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".