Bibliographic record
Abstract
A inovação social tem ganhado relevância no cenário internacional acadêmico com o surgimento, nos últimos 20 anos, de diversos grupos de pesquisa (CRISES, RQIS, TRANSIT etc.). Estes grupos têm se dedicado a estudar tanto os aspectos conceituais, referentes ao processo de inovação social, como para observar empiricamente o seu surgimento, barreiras e facilitadores. E no Brasil? O propósito deste artigo é avaliar se as mesmas questões centrais abordadas no exterior se aplicam a nossa realidade. Para tanto, foi realizada uma abordagem qualitativa de coleta e de observação de dados em quatro organizações que apresentaram algum tipo de inovação social no país. Como resultados, são destacadas diferenças significativas entre os casos estudados e as referências bibliográficas, indicando que precisam ser consideradas questões culturais no processo de inovação social, sensibilização e apoio de outros setores da economia, além do estabelecimento de um modelo de negócios claro, que se autossustente financeiramente.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".