Living, learning, working, and playing during COVID-19: tackling existing and exacerbated problems of low-income Singaporean youth
Bibliographic record
Abstract
COVID-19’s adverse, disproportionate impact on low-income youth — prompting youth-serving professionals to adapt and adjust — is well-documented. However, research gaps exist, including explanatory processes underlying COVID-19’s deleterious impact, systematic documentation of existing and exacerbated problems, and short- and long-term responses of youth-serving professionals. Using a multi-informant mixed methods design guided by a live-learn-work-play theoretical framework, exploratory findings indicated that COVID-19 worsened existing problems across all domains. In the short-term, Singaporean professionals prioritised, moved online, and evaluated programmes. Progressively, they sought to build youth communities, empower families, collaborate, and experiment. Findings have implications for understanding and resolving structural problems perpetuating pre-disaster vulnerabilities.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".