Aproximaciones metodológicas en la nueva normalidad para la investigación cualitativa en las áreas del diseño
Bibliographic record
Abstract
Es eminente, que la pandemia generada por el COVID-19 ha marcado un precedente en la vida diaria de todos los seres humanos y las universidades, no han sido la excepción. El objetivo de esta propuesta, es presentar algunos métodos y técnicas de acopio de información cualitativa, sobre el acopio de información centrada en el usuario, que pueden ser útiles para la nueva normalidad, en las áreas de la investigación del diseño. La metodología se desarrolló a través del uso de pruebas y sondeos culturales, aplicado al tema de violencia de género desde una perspectiva social de la mujer y la reproducción social de la vida cotidiana. Las conclusiones, son sobre la interpretación del material recolectado.
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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 | 0.068 | 0.087 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".