Bibliographic record
Abstract
From a social psychology perspective, principles of neoliberalism and dimensions of loneliness are positively associated across socioeconomic, sociopolitical, and sociocultural domains. Despite neoliberalism endorsing economic and entrepreneurial freedom, a persistent loneliness epidemic is in effect, as loneliness is linked to physical and psychological health risks. Drawing on theories rooted in community psychology, behavioural response models, and socioeconomic analysis, it is proposed that neoliberalism normalizes a culture of loneliness, enables loneliness behaviours and responses, and institutionalizes systemic alienation. Through a review of empirical quantitative and qualitative studies, it was found that conditions of neoliberal individualism produce feelings of loneliness and related health risks compared to conditions of collectivism. Divisive loneliness behaviours and maladaptive coping mechanisms are consequences of the neoliberal commodification of social interactions. Stigmatized alienation and the decline of an individual’s social value are the results of neoliberal emphasis on self-autonomy and entrepreneurship. The implications of these findings call for a return towards greater social cohesion, promotion of healthier participation in consumerism, and institutions making concerted efforts to utilize policies for the social benefit of individuals and communities. While a direct causal relationship between neoliberalism and loneliness is under-researched, the presented evidence in this article serves as a foundation for further investigation of the loneliness epidemic under a neoliberal capitalist context.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".