HACIA UNA PERSPECTIVA FILOSÓFICA, SOCIOLÓGICA Y ARQUEOLÓGICA DE LA DINÁMICA DE LAS CLASIFICACIONES PSIQUIÁTRICAS
Bibliographic record
Abstract
Las clasificaciones psiquiatricas son objeto de agitado debate epistemologico entre el realismo y el escepticismo taxonomico. En este trabajo se presenta una forma de reflexion sobre el tema de las clasificaciones que elude los aspectos metafisicos para enfocarse exclusivamente sobre la dinamica clasificatoria y sus procesos de retroalimentacion en tanto modeladores e incluso gestores de la identidad individual. Se senalan las valiosas contribuciones que, al respecto, han florecido desde tres vertientes anti-esencialistas y aparentemente desconectadas: 1) la microsociologia de Erving Goffman; 2) la arqueologia/genealogia de Michel Foucault; 3) la filosofia existencialista. Basicamente se revisan estas fuentes disciplinares cuyo ensamblaje ha renovado el planteamiento “nominalista” encabezado por el filosofo de la ciencia Ian Hacking en el campo de la psiquiatria, la psicologia y el psicoanalisis. El nodo de tal exposicion de ideas es el enfasis sobre la interaccion entre los expertos clasificadores, los pacientes clasificados y las propias categorias clasificatorias. Se argumenta que no solo acontece una modelacion de la subjetividad a partir de la etiquetacion, sino tambien la inversa: una modelacion de las etiquetas a partir de la subjetividad. Dicho ejercicio de exploracion filosofica obligaria a repensar las bases epistemologicas de los mas importantes manuales de clasificacion psiquiatrica (DSM, CIE). Palabras clave Psiquiatria Clasificacion Ian Hacking ABSTRACT TOWARDS A PHILOSOPHICAL, SOCIOLOGICAL AND ARCHEOLOGICAL PERSPECTIVE ON THE DYNAMIC OF PSYCHIATRIC CLASSIFICATIONS Psychiatric classifications are in the middle of dramatic epistemological debates between taxonomic realism and skepticism. In this paper a different approach is proposed about classifications in order to avoid some metaphysical aspects. It is focused on dynamic classificatory processes and a so-called feedback effect´ considered as relevant to the personal identity modeling. Valuable contributions are underlined, especially those thriven on anti-essentialist lands and -in appearance- disconnected: 1) the Erving Goffman´s microsociological analysis; 2) the Michel Foucault´s archeology / genealogy; 3) the existentialist philosophy. Basically, the assembly of these diverse disciplinary currents have innovated the nominalist conception leaded by the Canadian philosopher of science Ian Hacking in the psychiatric, psychological and psychoanalytic areas. The central point in this exposition is the emphasis on the interconnection among expert classifiers, the classified patients and the classificatory categories by own. It is argued that not only a modeling of subjectivity is developed from labeling process but also the opposite: a modeling of labels from subjectivity. A philosophical exploration like this forces us to rethink about epistemic foundations of the most important psychiatric classification manual (DSM, CIE). Key words Psychiatry Classification Ian Hacking
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.008 | 0.036 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 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".