Elite maintenance work across the Covid-19 crisis: a critical view on power and language
Bibliographic record
Abstract
Purpose This paper aims to present a critical interpretation of unfolding events related to corporate and policymaking elites during the coronavirus (Covid-19) pandemic crisis to serve as a point of contrast to mainstream views. Design/methodology/approach Drawing upon literature on elite maintenance and power, learning from recent previous crises and emerging evidence during the Covid-19 pandemic crisis, this study develops arguments to question and problematize the exercise of power by elites toward maintenance of existing systems across the pandemic. Findings Critical examination points attention to three related but analytically distinct strategies in the exercise of elite power: reinforcing myths, redirecting blame and reclaiming positions, all directed to maintain the system and preserve power. The potential effects of this ongoing elite maintenance are highlighted, revealing the old and new forms of power likely to emerge at the corporate, national and global levels across the pandemic crisis and endure beyond it. Social implications It is hoped that the critical examination here may build more awareness about the deep and complex nature of elite power and systems across the globe that preclude meaningful system change to address societal challenges. It may thereby provide more informed engagement toward system change. Originality/value The main originality of the paper lies in its attempt to tie together the various types of elite maintenance works and their potential effects into an overarching narrative. Making these connections and interpreting them from a critical perspective provides a rare large-canvas picture of elite power and system maintenance, particularly across a global crisis.
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.
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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.019 | 0.085 |
| Scholarly communication | 0.017 | 0.018 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".