Life in Islamabad and Rawalpindi During the Pandemic: Gender and Sector of Employment as Main Contributing Factors
Bibliographic record
Abstract
Covid-19 pandemic was a stress test to Pakistan’s healthcare systems, social policies, and political stability. This study explores Pakistanis’ lived experiences during the advent of the Covid-19 pandemic, including the impacts of Covid-19 on their livelihood, as well as their perceptions and opinions of their government’s policy measures. Through a questionnaire survey of 1000 participants living in the cities of Islamabad and Rawalpindi, this study found that livelihood, including food supply and household finance were main challenges facing many Pakistanis during the Covid-19 pandemic; and the level of vulnerabilities were tightly related to socio-demographic characteristics like gender, living arrangement, and sector of employment. Men are more likely to suffer from hunger, and men work in the informal sector and living in a multigeneration (or multi-nuclear household) tend to be more vulnerable than others. Almost all employed respondents reported income deduction and most of them reported the increase of household expenditure during the pandemic. The mixed opinions on the government’s Covid-19 measures and policies were associated to respondents’ socio-demographic characteristics. There were sharp gender differences as well. Men were more in agreement with the government’s policies than women, which implies a gender based information access disparity.
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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 | 0.003 | 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 | 0.000 |
| 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".