Bibliographic record
Abstract
Poucos questionariam o cenário desafiador da educação superior internacional, pesquisa e inovação (international higher education, research and innovation, IHERI) ou a crescente complexidade e interconectividade das relações entre os países. Contudo, paradoxalmente, há uma ausência de pesquisas sobre a intercessão destes dois fenômenos em evolução. Este artigo pretende abordar este tema, propondo o conceito de diplomacia do conhecimento ao invés do de soft power para entender o papel da IHERI na construção de relações baseadas em colaboração, reciprocidade e mutualidade de benefícios. Uma definição e um quadro conceitual da diplomacia do conhecimento são propostos e detalhados. Três iniciativas de IHERI– a Pan African University, a German Jordanian University e RENKEI – uma rede de pesquisa entre universidades japonesas e do Reino Unido – são examinadas para ilustrar como elementos e princípios fundamentais do quadro da diplomacia do conhecimento podem ser aplicados. O artigo finaliza questionando o futuro da diplomacia do conhecimento e a necessidade de outras pesquisas.
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 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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.013 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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; both teacher heads agree on what is shown here.
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".