Bibliographic record
Abstract
Neste artigo, os autores ilustram como os sujeitos criativos podem usar um aspecto específico do modelo Praxis Parallaxic da PaulineSameshima, o “Processo de Catequização”. Eles descrevem os passosprocessuais e as possibilidades de catequese, um processo que a Sameshima desenvolveu para promover o significado e a geração de criatividade na pesquisa. O processo beneficia sujeitos criativos em vários campos e pode ser aplicado sempre que as investigações ocorrem por meio da criação em artes. Nesta explicação, os autores compartilham sete poemas de resposta criados no Processo de Catequização para teorizar o espaço imaginativo de produzir conhecimento por meio da investigação. Quando pesquisadores podem se imaginar como sujeitos criativos e experimentam mais estratégias para gerar novas ideias, seu trabalho abre novas possibilidades de compreensão.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.028 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".