Carta a um Jovem Terapeuta: “Pessoas Iniciam Terapia para Nao Mudar”
Bibliographic record
Abstract
This article is the first letter of a book of seven letters to a young therapist (Di Nicola, 2011) which won the prestigious Prix Camille-Laurin of the Association des medecins psychiatres du Quebec. In these seven letters, the author offers wisdom to a young therapist from 25 years of experience conducting relational therapy. Di Nicola’s book complements his model of working with families across cultures presented in Um Estranho na Familia: Cultura e Terapia (Di Nicola, 1997/1998). This first letter addresses questions about reading Freud and when therapy begins. People come into therapy in order not to change, meaning they want to maintain coherence. As a result, we must find gentle ways of approaching them, so I describe my first tool for family therapy: spirals. The fact that people do not always choose to enter therapy is discussed as well as the question of technique. A novelist’s explanation of what narrative does to our understanding by removing curtains” that obscure our understanding of human phenomenology highlights what we do in therapy. This is contrasted to our age of technopoly which wants to reduce everything to technique, to what can be measured, in a war against subjectivity and human judgment
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".