Protocolo verbal: análisis de la producción científica, 1941-2013
Bibliographic record
Abstract
Introduccion: el protocolo verbal es una tecnica introspectiva de recoleccion de datos durante la ejecucion de una tarea en la que el sujeto verbaliza en voz alta su proceso de pensamiento. Se pretende conocer cuales son las disciplinas cientificas que estan usando o han utilizado la metodologia del protocolo verbal. Metodos: para ello, se realizo una busqueda en las bases de datos de la Web of Science y SCOPUS usando la estrategia thin* alou*. Resultados: se recuperaron 1.481 documentos, extrayendo variables para analizar la produccion cientifica (autorias, instituciones, revistas) y categorias tematicas, asi como un analisis especifico de los ochenta y dos articulos localizados que provienen de investigadores del area de Biblioteconomia y Documentacion. Conclusiones: se concluye que es una tecnica que ha sido usada cerca de setenta y cinco anos, principalmente para realizar investigaciones en el ambito universitario desde los Paises Bajos, Estados Unidos y Canada en Psicologia, Educacion y Medicina, pero tambien en otras areas como Computacion, Ergonomia, Ciencia de la Informacion y Biblioteconomia, Enfermeria, entre otras.
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 | 0.093 | 0.343 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.015 | 0.018 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.120 | 0.022 |
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".