African Emerging Adult Resilience: Insights From a Sample of Township Youth
Bibliographic record
Abstract
What enables the resilience of African emerging adults who live in sub-Saharan Africa and must contend with an everyday reality that is characterized by structural disadvantage and related hardship? This question directed the exploratory qualitative research that we report in this article. Its genesis was the relative inattention to the resilience of African emerging adults—that is, young people living in sub-Saharan Africa, aged 18–29. To answer this question, 16 South African participants (average age 21) from a significantly stressed community participated in group interviews and generated digital stories. A deductive analysis of the content yielded the understanding that the self is central to emerging adult resilience. Family members mattered too, but there was scant reference to any other social or ecological resource. These findings urge attention to the dangers to resilience if social ecologies are not resourced to better co-facilitate positive outcomes for disadvantaged emerging adults.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".