The Authoritarian Populism and Social Pathologies Pulling Democracies Apart
Bibliographic record
Abstract
The vast, entrenched inequality caused by globalization has created a deep sense of alienation within electorates suffering from social breakdown, fractured realities, and a loss of faith in the democratic process. Into this gap have jumped uncompromising strongmen who seek to tear down institutional checks and balances of power through a coherent set of anti-democratic tactics that appeal to maligned and disaffected populations. As a result, the transformative changes that numerous democratic societies are undergoing will render them less capable of dealing with the overarching global challenges presented by both the coronavirus pandemic and accelerating climate change. This article seeks to build upon a well-established line of thought within sociology around reasons for the backlash against globalization by offering analysis of how the resulting economic and social change in democratic societies everywhere has followed a practiced, over-arching strategy—one that leverages hyper-individualist views of reality. For evidence, it weaves together a range of intellectual commentary, cultural theory, research reports, journalistic accounts, statistics, and current affairs. The article ends with a call for citizens and scholars alike to connect disparate forms of struggle with one another as a means to rebuild the collective empathy and imagination necessary to solve shared problems.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.018 | 0.087 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".