Desenvolvimento, inovação e aprendizagem : avaliação da trajetória do Grande ABC
Bibliographic record
Abstract
This thesis consists of a case study on the experience of the Greater ABC Region towards a Regional Innovation System (RSI). It is sought, from this study, to identify possibilities and limits for the construction of such Systems. Since 1990, public and public-private articulated institutions of regionality were created by the main social actors of the Region, constituting an original regional experiment. After a quarter of a century, there are discrepancies in the results of such entities. In terms of public policies articulated among the seven municipalities wich compound the Region, there were important advances. Regarding the territorial economic development based on universities, industries, local governments and unions interactions, towards innovation and productive diversification, the Region has achieved far more limited results. In order to understand these disparities, a research was carried out focusing on statistics, documents and interviews of personalities from the Region at the four activity segments mentioned. The results were interpreted based on the neoschumpeterian and regulationist frameworks, which made possible significant advances in the understanding of the regional problematic. Nevertheless, certain silences and gaps intrinsic to such theoretical strands were observed. Therefore, after presenting the main results achieved, a proposal for an additional research path is suggested, aiming to overcome those limitations of the theoretical paradigms adopted.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".