Care Ethics in Universities: Beyond an Easy “Add and Stir” Solution
Bibliographic record
Abstract
El trabajo de Nel Noddings ha representado un profundo desafío para el pensamiento androcéntrico en filosofía de la educación. El documento plantea la cuestión de si la ética del cuidado podría agregarse a las políticas universitarias. Para lograr este objetivo, se explora si la incorporación de la ética del cuidado en las políticas universitarias transformaría la orientación de la investigación, la administración universitaria y la experiencia de aprendizaje en tu totalidad. Más adelante, el documento analiza las implicaciones del significado de la ética del cuidado de Noddings como un vía para abordar la moralidad aplicada a los entornos universitarios. Finalmente, el artículo concluye ofreciendo la ética del cuidado como una alternativa a las teorías éticas tradicionales en base a sus puntos fuertes que convergen en la posibilidad real de formar mejores adultos.
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 | 0.032 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.022 | 0.072 |
| Scholarly communication | 0.025 | 0.033 |
| Open science | 0.003 | 0.031 |
| Research integrity | 0.023 | 0.021 |
| Insufficient payload (model declined to judge) | 0.014 | 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; 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".