Bibliographic record
Abstract
Abstract Using Q-methodology, Mackay's (1995) study sought to find empirical support for the three-stage model of the Gestalt two-chair technique and the theory put forth by Greenberg (1979, 1983) and Greenberg, Rice, and Elliot (1993). A structured Q-sort was constructed using the factors of conflict resolution (CR) and the Gestalt concept of contact (C) in a 2×2 factorial design. Each factor was divided into two levels: CR—resolved versus unresolved and C—contact versus interruption of contact. The factors of CR and C were expected to interact before and after successful and unsuccessful therapy for decision making. Eight participants who were ambivalent about staying married performed the Q-sort before and after six sessions of therapy in which the two-chair technique was used as the primary intervention to facilitate their pre-decision making regarding their marriage. Moderate support was found for the three stages of the model: opposition, merging, and integration. When therapy was successful, the factors of CR and C interacted as predicted. When therapy was not successful, the factors of CR and C did not interact as predicted. The factors of CR and C did not interact for individuals who were experiencing a great deal of interruption of contact, indicating there is a possible prestage to the model.
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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".