Governance score for local innovation and production systems in the state of Paraná: contribution to regional development
Bibliographic record
Abstract
The present dissertation addresses the agglomeration economies and their cumulative processes in the State of Paraná from an approach that focuses on the issue of Paraná’s geographic space. This conceptual approach converges with the concept of Local Productive Arrangements (APLs) adopted by this study. Thus, this work returns its analytical focus to APLs, their territorialization of productive structures and their local governance. Immersed in this scenario and bearing in mind the objectives established for the elaboration of this work, given the importance assumed by governance in the conduct of local productive arrangements, the practical applicability of the research is in the promotion of discussions that can help in the configuration of public policies aimed at leveraging regional development in the Paraná scenario. Using methods and techniques of regional analysis focusing on measures of location and specialization, it seeks to characterize the regional patterns of spatial distribution of service activities in the Information and Communication Technology (ICT) sector in the State of Paraná. For its development, this study used secondary data available in the Annual List of Social Information (RAIS) with a quantitative approach to the formal jobs generated by this sector in the territory of Paraná between 2013 to 2021. It also describes the methods used in data collection and the calculations to obtain the location coefficient. The results converge to the understanding that there is still a need to reconfigure public policies to promote territorial agglomerations and the National Policy for Regional Development (PNDR) in the public consultation process for its revision. In the same perspective, territorial governance must be understood as an essential component of proposing strategies for regional development. The conclusions from the analysis of the data contained in the RAIS with a quantitative approach to the formal jobs generated by this sector in the territory of Paraná in the mentioned period corroborate the perception of the need for a spread in the productive sectors and, at the same time, in the permanent search for policies public policies that ensure the effectiveness of territorial governance.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".