Relational Hypnotherapy for a Phobia of Blood and Needles: A Context-Enriched Conversation Analysis
Bibliographic record
Abstract
Although clinical hypnosis has been studied in a variety of ways, most researchers have focused on individual approaches; few have examined relational models influenced by Gregory Bateson's systemic concepts. This article explores how the second author, the developer of a relational approach to hypnotherapy, successfully helped a client who desired to have a baby but could not see or talk about blood, needles, or medical procedures without fainting. Using context-enriched conversation analysis (CECA), the authors examined multiple sources of data, including selected audio-recorded excerpts from the hypnotherapeutic sessions; the client's descriptions of change in her email correspondence with the second author; and the second author's case notes. Although there were a total of eight sessions, this article primarily concentrates on what transpired during the first two sessions of a single case. The authors address clinical and research implications for hypnosis, brief and family therapy, and psychotherapy in general.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".