Gender analysis of future aspirations, resilience and adaptation capability of Nigerian youths in the post COVID-19 era
Bibliographic record
Abstract
Following the global pandemic, understanding the resilience ability of male and female youths becomes imperative towards attaining their future aspirations and building their adaptation capability for future recurrent shocks and crises. There is a dearth of empirical studies on male and female youths’ future aspirations, resilience and adaptation capability in Nigeria. This study engenders Nigerian youth's future aspirations, resilience and adaptation capability after the COVID-19 pandemic. A cross-sectional survey was conducted among youths aged 15–35 in Nigeria's six geo-political zones. Quantitative data were collected using the surveyCTO mobile app by trained enumerators from the youths (M age = 27.15 years, SD = 5.87; 50% female). Descriptive and inferential statistical tools such as means, percentages and t-test were used for data analysis. COVID-19 negatively impacted male (68.9%) and female (60.1%) youths’ future aspirations. The economic aspect of male (86.7%) and female (81.6%) youths’ future aspirations was the most affected. Both male and female youths have high resilience and adaptation capability. However male youths were more adjustable and resilient to changing situations than females. The adaptation capability of males was significantly higher than females. The strength of Nigerian youth for continuity in pursuing their future aspirations draws on their undaunting adaptive and resilient capabilities during uncertainties. Youth policies and intervention programmes should focus more on economic empowerment and the building of females' adaptive and resilience abilities to enhance their cognitive ability and emotional strength in the post COVID-19 era.
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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 | 0.000 | 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 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".