Bibliographic record
Abstract
The chronological development of Freud’s theories of anxiety is reviewed in connection with the series of infantile danger-situations, the distinction between traumatic and signal anxiety, and the defenses evoked by the latter to avoid the former. The central defense of turning aggression away from the object and back against the self, thus generating the hostile superego, is emphasized. A critique of Freud‘s one-sided conception of danger as loss of the good is offered in light of Melanie Klein’s recognition of the danger constituted by the presence of something bad. In light of the shift from topographical to structural theory additional types of anxiety are distinguished: instinctual anxiety experienced by the ego in the face of the Id; Reality anxiety in the face of the external world; moralistic anxiety in the face of the superego. While Freud failed to distinguish persecutory and reparative anxiety and guilt, Klein and her followers posited two fundamentally different layers or positions in the mind, the paranoid-schizoid and depressive or reparative positions characterized by these two types of anxiety and guilt respectively. There has been a good deal of confusion due to the widespread failure to distinguish depressive anxiety from depression: there is no depression in the depressive position because the splitting involved in depression is a paranoid-schizoid phenomenon. The existentialists remind us that not all anxiety and guilt is neurotic.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.021 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".