Bibliographic record
Abstract
La psicopatía es un concepto resultante de la confluencia de distintas tradiciones psiquiátricas alemana, francesa y anglo americana. A partir de las investigaciones de Robert Hare en Canadá, se logró la operacionalización y medición a través de la Hare Psychopathy Checklist – Revised (PCL-R). La psicopatía es un diagnóstico que hace referencia a la forma de vida de un sujeto y ha tenido variaciones en sus connotaciones y dificultades en su operacionalización por lo que muchas veces aparece ligado al concepto de perversión.El presente trabajo tiene el propósito de esclarecer el diagnóstico de psicopatía a través de la valoración por medio del juicio clínico estructurado, lo que implica el uso de una técnica mixta clínico-actuarial (Pueyo y Redondo Illescas, 2007) como lo es la PCL-R, que de ninguna manera sustituye el conocimiento, la experiencia y las habilidades clínicas, sino que su utilidad reside en el uso como herramienta al servicio del clínico para la recolección y valoración de los datos.El esclarecimiento del constructo de la psicopatía y la utilización de la PCL-R nos proporcionaran los elementos diagnósticos diferenciales relativos al concepto de perversión, tal y como se teoriza en el psicoanálisis francés.Psychopathy is a concept resulting from the confluence of different traditions psychiatric German, French and Anglo American. From the research of Robert Hare in Canada, it was possible to operationalize the concept and measurement through the Hare Psychopathy Checklist - Revised (PCL-R). Psychopathy is a diagnosis that refers to the way of life of an individual and has varied in its connotations and difficulties in its operationalization by what often appears to be linked to the concept of perversion. This paper aims to clarify the diagnosis of psychopathy through assessment through structured clinical judgment, which involves the use of a clinical-actuarial mixed media (Pueyo and Redondo Illescas, 2007) such as the PCL-R, which in no way replaces the knowledge, experience and clinical skills, but its usefulness lies in the use as a tool for the clinician to the collection and evaluation of data.Clarifying the construct of psychopathy and the use of the PCL-R we will supply the differential diagnosis concerning the concept of perversion, as theorized in French psychoanalysis.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".