Wise reasoning and political leadership amid COVID-19 pandemic: an exploratory study on Ghana
Bibliographic record
Abstract
Purpose This paper examines how one group of frontline health workers (nurses) amid coronavirus disease 2019 (COVID-19) pandemic perceive the Government of Ghana (GOG)'s decision to ease the lockdown restrictions when cases were increasing. This paper contributes to the literature on Igor Grossman's concept of wise reasoning and its applicability to COVID-19 management decision-making by political leaders. Design/methodology/approach The paper employed an exploratory qualitative design. The decision to adopt qualitative method is linked to the paucity of research on wise reasoning, political leadership and COVID-19. The paper draws on qualitative online survey with 42 nurses located in Accra Metropolis, Ghana. Findings The paper demonstrates that a confluence of research participants perceived the government's act of easing the lockdown restrictions to be in bad faith on account of (1) nonrecognition of different perspectives and viewpoints from stakeholders and interest groups; (2) rising number of cases which naturally make the decision to lift the restriction unwise; (3) concerns about the prioritization of peripheral issues over citizens' health and (4) concerns about limited and robust health facilities and their implications. Research limitations/implications The key claims must be assessed against the limitations of the study. First, the study is an exploratory study and, therefore, not intended for a generalization purpose. Second, the research participants are highly educated, and the responses in this study are skewed toward them. Originality/value The paper is novel in seeking to explore wise reasoning and political leadership during a global pandemic such as COVID-19. This exploratory study demonstrates that COVID-19, though devastating and causing havoc, presents an opportunity to test Igor Grossmann's wise reasoning framework about decision-making by political leaders. This extends the literature on wise reasoning beyond the discipline of psychology (the fact that all the authors are geographers) and Global North to Global South since the data for this study are gathered in Ghana.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".