What<scp>COVID</scp>‐19 tells us about the self: The deep intersubjective and cultural layers of our brain
Bibliographic record
Abstract
The COVID-19 crisis is affecting our sense of self and touches upon our existential fears. This extends to the self-other relationship, as there is both being infected and infecting the other. What does this pandemic crisis tell us about our self and relatedness, its cultural differences, and how these are rooted in the brain's relation to the world? First, we discuss the psychological and neuronal features of self and self-other relation and how they are rooted in a deeper layer of the brain's neural activity complementing its cognitive surface layer. Second, we demonstrate cultural differences of Eastern and Western concepts of the self (i.e., independency and interdependency) and how these reflect the manifestation of the brain's neuro-social and neuro-ecological alignment. Finally, we highlight the intersubjective and cultural nature of the self and its surface in the COVID-19 crisis. Discussing various lines of empirical data showing the brain's intimate alignment to both social and ecological environmental contexts, our results support the assumption of the brain's deep layer features by laying bare a continuum of different degrees of neuro-social and neuro-ecological alignment. This entails a two-stage model of self with neuro-social-ecological and psychological levels that extends the previously suggested basis model of self-specificity. We conclude that the current pandemic shows the importance of the deeper intersubjective and cultural layers of both the self and brain; their neglect can be life-threatening for the self and others and, paradoxically, might reduce, rather than enlarge, the self's sense of freedom and independence.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".