COVID-19, Norms, and Discrimination against Female Gender in Nigeria: Focus on Implications for Mental Health Counselling
Bibliographic record
Abstract
The COVID-19 outbreak is inflicting different societies of the world with an untold and unprecedented hardship. However, the extent of impacts is bound to differ across groups, gender, economies, and countries. Given how the pandemic affects particular groups, this paper focuses on girls/young women and how Covid-19 may further strengthen gender norms and discriminations as risk factors of their mental health. In some societies, right from birth, the life experiences of the female child differ from the male child. At every stage of development, girls are more likely than boys to confront a host of challenges associated with discrimination and norms, which are gender-based. With the effects of the current pandemic evident in reduced access to health care, education, teenage pregnancy, and being vulnerable, young women and girls are more at the receiving end of their impacts. These stand as hindrances to the girl child's mental health because they tend to constitute anxiety, depression, self-harm, or even suicide and weakens her will power to make proper adjustment to life issues. This paper concludes that given that the impacts of COVID-19 are not gender-blind (affecting both genders), therefore the designing policy responses to the current pandemic should not be either. As we all continue to face this overwhelming Covid-19 pandemic, the study recommends that the vulnerable (especially girls and young women) should not be neglected or ignored. This is possible by not forgetting the inequalities that may worsen the conditions of girls because of the crisis
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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 | 0.000 | 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 | 0.000 | 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".