The insecure skin‐ego: Conspiracy theories as a source of containment in a pandemic
Bibliographic record
Abstract
Abstract In analyzing the psychological reactions to the recent COVID‐19 pandemic, we have tried to show that the existing societal protective skin that gives unity to people by creating a secure containment was too thin and fragile to cope with an annihilation situation such as the pandemic. This healthy and protective societal skin acts continuously as a maternal environment, providing physical and mental security. As a modest contribution, we provide psychoanalytic, social, cultural, and political analyses of the conspiracy theories and infodemics in the mid‐COVID‐19 era. We extend Anzieu's theory of skin‐ego from a maternal‐centered conceptualization to one based on a wider range of caregivers, including politicians, health care professionals, scientists, and researchers—who act as the suppliers of containment. During the pandemic, the common protective skin showed initial flexibility as it tried to regenerate a secure common skin with the help of the health care system and other state organizations responsible for managing the COVID‐19 pandemic. However, the common protective skin is under continuous attack by various politicians around the world, like the hyper‐masculine figure of Donald Trump who attacked this common skin, increasing the insecurity and helplessness of people. Like hermit crabs, thin‐skinned people with insecure skin‐egos sought refuge inside the shell of Trump's safer and thicker skin. A shell of conspiracy theories and infodemics provided by crustacean Trump functioned as a thick, protective skin. To illustrate our ideas, we present events and reactions from the pandemic and also cite two illustrative examples—the story of Noah's Ark and the children's classic, The Three Little Pigs.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.044 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 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".