Social work undergraduates students and COVID-19 experiences in Nigeria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Following the highly contagious nature of the coronavirus disease and the increase in confirmed cases, the Nigerian government, imposed lockdowns, quarantines, and various social distancing measures to curb the rate of infection. Schools were closed, and examinations were postponed indefinitely. Students of private schools were able to resume academic activities online. However, most public schools could not do so, due to lack of infrastructure. This study aimed to qualitatively investigate the impacts of the novel coronavirus on final-year students of social work, at the University of Nigeria. Data was collected from 20 undergraduates using in-depth interviews. Findings showed that the pandemic had negative effects on different aspects of the students' lives. It was also revealed that some of the students were resilient and were able to use various coping strategies to avoid being overwhelmed by the situation. A policy implication of this study is the need for revitalization of Nigerian public universities, as the continued lockdown of schools shows how public universities are poorly managed in the country. This poor management of public schools has made it impossible for a switch to virtual learning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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 it