ENTRE L’UNIVERSITÉ ET LES COLLECTIVITÉS LOCALES: COMMENT S’EFFECTUE LE PARTAGE DES CONNAISSANCES?
Bibliographic record
Abstract
Tanto no Brasil quanto no Canadá, o compartilhamento de conhecimento entre universidades e coletividades tem tido maior ou menor sucesso. Tentar revelar os mecanismos viáveis dessa troca de conhecimento é fundamental para transferir as lições dessas experiências de um país ao outro. Este estudo comparativo foi realizado por uma rede de instituições canadenses e brasileiras – o BRACERB – e trata das experiências de compartilhamento de conhecimento universidade-coletividade empreendidas por instituições dessa rede. Para se poderem comparar essas experiências, são inicialmente definidos alguns conceitos: comunidade, coletividade, desenvolvimento sustentável, ecodesenvolvimento, desenvolvimento local, território e empoderamento. A seguir, são analisados onze estudos de casos, com o objetivo de identificar os problemas e as modalidades do diálogo coletividade-universidade. As principais conclusões desta análise são: (i) os serviços de extensão são fontes de inovação social e de empoderamento das coletividades; (ii) as redes entre a universidade e outros atores do desenvolvimento tornam-se necessárias à real democratização do conhecimento. O empoderamento dos atores sociais constitui uma nova via pela qual a universidade “aprende” e “compreende” o desenvolvimento local e contribui para a construção deste.Palavras-chave: compartilhamento de conhecimento; empoderamento; desenvolvimento local; inovação social; redes sociais.Résumé: Au Brésil et au Canada, le partage des connaissances entre universités et collectivités a connu un succès variable. Tenter de dégager les mécanismes viables de ce partage est fondamental pour transférer les leçons de ces expériences d’un pays à l’autre. Cette étude comparative a été menée par un réseau d’institutions canadiennes et brésiliennes – le BRACERB – et porte sur les expériences de partage de connaissances université-collectivité réalisées par des institutions membres de ce réseau. Afin de pouvoir comparer ces expériences, certains concepts sont préalablement définis: communauté, collectivité, développement durable, écodéveloppement, développement local, territoire et empowerment. Onze études de cas sont ensuite analysées en tentant de discerner les enjeux et les modalités du dialogue collectivité-université. Les principales conclusions qui ressortent de cette analyse sont que les services à la collectivité sont sources d’innovation sociale et d’empowerment des collectivités. De même, il en ressort que le réseautage entre l’université et les autres acteurs du développement devient nécessaire à la démocratisation réelle des connaissances. L’empowerment des acteurs sociaux constitue une nouvelle avenue par laquelle l’université «apprend» et «comprend» le développement local et contribue à sa construction.Mots-clés: partage de connaissance; empowerment; développement local; innovation sociale; réseautage.Abstract: In Brazil and Canada, university-community knowledge sharing is relatively successful. By aiming at common goals, it takes places according to different models rooted in specific institutional structures and cultural systems. This comparative study, undertaken by the BRACERB network analyzes eleven cases so as to determine the stakes and the manners through which university – community dialogues take place. The results demonstrate that university outreach is a source of social innovation and empowerment and that networking between universities and other social actors democratize the sharing of knowledge. Through the empowerment of societal actors, the university “learns” and “understands” local development and contributes to its progress.Keywords: knowledge sharing; empowerment; local development; social innovation; networking.
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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.001 |
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".