Operacionalização da teoria dos ciclos de vida dos clusters. As indústrias criativas como contexto para a reflexão e o Software Educacional e de Entretenimento no Norte de Portugal como caso de estudo.
Bibliographic record
Abstract
Este artigo propõe uma reflexão sobre a dinâmica evolutiva dos clusters, à luz da teoria do ‘ciclo de vida dos clusters’ (CVC), e sobre os elementos adequados para captar, na prática, essa mesma dinâmica. Partindo de uma revisão da literatura, o estudo centra-se depois na análise de um cluster organizado - Software Educacional e de Entretenimento no Norte de Portugal. A revisão da literatura e a análise do estudo de caso permite concluir que, apesar do crescente reconhecimento da relevância dos fatores soft (ex. capital social, redes) na dinâmica de um cluster , esta tende a ser frequentemente analisada a partir de dados estatísticos relacionados com o seu crescimento. Propõe-se por isso um modelo analítico capaz de combinar elementos quantitativos e qualitativos, e que permite comparar as diferentes trajetórias de evolução dos clusters . http://dx.doi.org/10.17127/got/2013.4.012 Data de submissão: 2013-09-12 Data de aprovação: 2013-12-06 Data de publicação: 2013-12-30
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".