Movilidad residencial estudiantil durante la pandemia del covid-19: Diferencias y similitudes entre dos casos internacionales
Bibliographic record
Abstract
Este artículo presenta un análisis de las motivaciones de los estudiantes universitarios de Montreal (Canadá) y Temuco (Chile) para cambiar de residencia durante la pandemia de COVID-19. Aplicando una metodología cuantitativa basada en el Análisis de Componentes Principales se identifican paralelismos construidos sobre motivaciones familiares, de bienestar, económicas y de necesidades materiales. Sin embargo, en una segunda etapa, al indagar entre las similitudes y diferencias de cada uno de los colectivos según sus motivaciones, se ha reconocido un mayor número de diferencias, quedando las similitudes enmarcadas solamente en el contexto de las motivaciones familiares. Para desarrollar esta investigación se han aplicado más de 1.300 encuestas a estudiantes universitarios de estas dos ciudades durante la pandemia, permitiendo los resultados generar una panorámica muy completa de los efectos de la pandemia sobre la movilidad estudiantil, lo que constituye un avance innegable en los trabajos sobre estudiantización y las geografías estudiantiles.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".