Bibliographic record
Abstract
El uso de este término sugiere una educación dirigida hacia el empleo, que se sitúa precisamente en la intersección entre escuela y trabajo.Aunque, sin decir palabra, hemos pasado, solamente por el uso del vocablo, de la educación al trabajo, de la sociología de la educación a la economía del trabajo.2 La importancia dada al campo de la formación, de ahora en adelante, orienta investigaciones empíricas, alimenta representaciones y justifica discursos y medidas políticas.Los juicios "profanos" y "científicos" chocan contra el enfoque de la atención atribuida, en el período de desempleo durable, a la inserción profesional y, dentro de este campo, a la noción de competencia.La competencia, término ya rico de ambigüedades, se carga de significaciones nuevas, suscita la curiosidad, es investida de funciones múltiples y se generaliza en diversos medios.Ella se difunde y se impone en las esferas de la escuela y del empleo, inspira medidas de reforma de la enseñanza y la evaluación de los dispositivos de disminución del desempleo, hasta convertirse en el fundamento de la formación.El objeto de la formación se convierte en la adquisición de competencias.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.078 | 0.036 |
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".