The Intimate Geographies of Panic Disorder: Parsing Anxiety through Psychopharmacological Dissection
Bibliographic record
Abstract
The category of panic disorder was significantly indebted to early psychopharmacological experiments (in the late 1950s and early 1960s) by the psychiatrist Donald Klein, in collaboration with Max Fink. Klein's technique of "psychopharmacological dissection" underpinned his transformation of clinical accounts of anxiety and was central in effecting the shift from agoraphobic anxiety (with its spatial imaginary of city squares and streets) to panic. This technique disaggregated the previously unitary affect of anxiety-as advanced in psychoanalytic accounts-into two physiological and phenomenological kinds. "Psychopharmacological dissection" depended on particular modes of clinical observation to assess drug action and to interpret patient behavior. The "intimate geographies" out of which panic disorder emerged comprised both the socio-spatial dynamics of observation on the psychiatric ward and Klein's use of John Bowlby's model of separation anxiety-as it played out between the dyad of infant and mother-to interpret his adult patients' affectively disordered behavior. This essay, in offering a historical geography of mid-twentieth-century anxiety and panic, emphasizes the importance of socio-spatial setting in understanding how clinical and scientific experimentation opens up new ways in which affects can be expressed, shaped, observed, and understood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.035 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".