X’s and Y’s in the Midst of the Pandemic: Generational Identity, Mental Well-being and Life Satisfaction Among Filipino Adult Learners
Bibliographic record
Abstract
The 2019 novel Coronavirus disease (COVID-19) has increased the mental health challenges and decreased the quality of life among students and the general adult population. However, adult learners and non-traditional students who are currently at their quarter and midlife during the pandemic, remain underrepresented in well-being research. Moreover, the unique sociocultural and historical contexts specific to generational cohorts may have an impact on the way they experience and cope with the challenges brought about by the pandemic. This study sought to determine the relationships among generational identity, mental well-being and life satisfaction among Millennial and Generation X Filipino adult learners. A total of 543 adult learners participated in this online cross-sectional study. Findings suggest that young millennials reported lower levels of mental well-being and life satisfaction compared to old millennials and Gen Xers. Moreover, mental well-being was found to be a predictor of life satisfaction among Filipino adult learners, regardless of their generational identity. Schools must implement initiatives to monitor and address mental health issues among adult learners, contextualized to quarter and midlife contexts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".