Cuando la experiencia secuestrada se subleva: Sobrevivir la pandemia
Bibliographic record
Abstract
El artículo examina el impacto, a nivel académico y personal, de la pandemia Covid-19 en estudiantes de Ciencias Sociales de la Universidad Nacional Mayor de San Marcos (UNMSM) con el fin de establecer una agenda de investigación con perspectiva de género. Testimonios y conversaciones informales revelan, que el bienestar emocional y cognitivo se ha visto principalmente afectado a raíz de múltiples pérdidas, condición de encierro, contracción del presupuesto familiar lo que lleva al quiebre de la confianza básica. Adicionalmente, los resultados de una encuesta-diagnóstico aplicada en abril 2021 en conjunción con el Decanato de la misma Facultad permiten vislumbrar, dificultades en la gestión del tiempo y falta de condiciones adecuadas de estudio, a lo que se suma el incremento de las horas invertidas en tareas domésticas y labores de cuidado de familiares dependientes. Los hallazgos muestran igualmente la gran oportunidad que significa la pandemia para recrear una nueva normalidad.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".