Imagining the Post-COVID-19 Polity: Narratives of Possible Futures
Bibliographic record
Abstract
The COVID-19 crisis is arguably the most important development of the 21st century so far and takes its place alongside the great eruptions of the past century. As with any crisis, the current pandemic has stimulated visions and proposals for post-COVID-19 societies. Our focus is on narratives—both predictive and prescriptive—that envisage post-COVID-19 political societies. Combining narrative analysis with thematic analysis, we argue that societal changes conditioned by the pandemic have accelerated a turn toward five inter-related developments: A renaissance in rationality and evidence-based science; a return to social equality and equity, including wage equity and guaranteed incomes; a reimagining of the interventionist state in response to crises in the economy, society, the welfare state, and social order; a reorientation to the local and communitarian, with reference in particular to solidaristic mutual aid, community animation, local sourcing, and craft production; and the reinvention of democracy through deep participation and deliberative dialogical decision making. The empirical focus of our work is an analysis of predominantly legacy media content from the Canadian Periodicals Index related to life after the pandemic and post-COVID-19 society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.037 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".