Relaciones sociales y trayectorias biográficas: hacia un enfoque comprensivo de los modos de influencia
Bibliographic record
Abstract
El objetivo del presente texto es proponer algunos elementos para un enfoque comprensivo de la influencia de las relaciones en las trayectorias biográficas. El análisis se apoya en los datos de un estudio longitudinal sobre el papel que desempeñan la familia y las redes en la perseverancia en los estudios, realizado con 96 jóvenes que inician su trayectoria postsecundaria. En lugar de abordar la influencia en términos de características sociales, o a partir de un enfoque estructural de las redes, proponemos aquí tratarla bajo el aspecto de las relaciones sociales y el sentido que toman éstas para los sujetos. Este enfoque permite examinar de qué manera se imbrican la influencia en la relación y la relación en la influencia, aclarar mejor ciertas dinámicas de las relaciones en un contexto de bifurcación biográfica, y esclarecer el papel que desempeñan las relaciones en la agencia de los individuos. También permite resaltar el papel importante que desempeña la historia compartida en la influencia de las relaciones sobre la trayectoria biográfica. Abstract:This paper analyses the influence of relations in biographic trajectories. It is based in a longitudinal analysis on the role of the family in the studies of 96 youth people after Secondary School. It analyses selection and influence processes, as well as the dynamics of relations in a context of biographical bifurcation. The role of relations and agency is also debated. The study emphasises the role of a shared history in the influence of relations on the biographical trajectory.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".