High performing male and female engineering students in Chile: accounting for mental health and well-being from a developmental paradigm
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mental health and well-being among high-performing male and female engineering students were investigated to account for variance. A self-report survey was used to assess mental health and well-being, and the results of the end-of-year evaluation were used to measure academic accomplishment. This study was unique in that it created the self-reported survey from a developmental viewpoint (i.e., developmental strengths, constructive skills, and psychological competencies) using the normative-crisis model and the psycho-social model of development. Of the 152 (121 male, 31 female) University students from Chile, twenty high-achieving male and female students were randomly selected. The findings showed that female students scored lower in all subjects, reported lower levels of hope and reported more mental health concerns than male students. Structural equation modelling (SEM) analysis of female students’ results found that lower hope levels and higher developmental strengths were associated with high academic achievement. However, mental health issues and psychological competencies among females did not influence higher achievement. In contrast, SEM analysis of male students’ results found no correlation between academic achievement and mental well-being, which suggests that high academic achievement is independent of sex differences, mental health and well-being. Insights, implications and recommendations are discussed.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it