Attachment Anxiety and Covert Narcissistic Pangs as Reflected in Tennessee William’s The Glass Menagerie
Bibliographic record
Abstract
This paper aims to provide an interdisciplinary space for fruitful debate concerning psychoanalytical representations of attachment anxiety and the fear of abandonment of a covert narcissist within the ambit of narcissism, and its implications in artistic, literary, and health discourses. Researchers in psychiatric, clinical, developmental, personality, and social psychology are interested in the issue of narcissism since its resurgence has hit the world on a pandemic scale in the last few years. Despite the extensive research on the construct of narcissism conducted so far, one of its under-represented clinical subtypes, "covert narcissism," which is intrinsically intertwined with the fear of abandonment and attachment anxiety (Cramer, 2019) remains largely unexplored as opposed to its counterpart, grandiose narcissism. Extending this hypothesis, the primary objective of the current scholarly investigation is to examine the correlations underlying the maladaptive attachment anxiety and fear of abandonment that Amanda Wingfield, the female protagonist of Tennessee Williams's most autobiographical play, The Glass Menagerie, wrestles with in her interpersonal and intrapersonal relationships. The study's secondary purpose is to further scrutinize and unearth a slew of unconscious yet toxic expressions of covert narcissism that Amanda embodies in her machinations to remain in her 'secure base'.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| 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".