Explanatory Styles of Counsellors in Training
Bibliographic record
Abstract
Abstract Explanatory style is based on how one explains good and bad events according to three dimensions: personalization, permanence, and pervasiveness. With an optimistic explanatory style, good events are explained as personal, permanent, and pervasive, whereas bad events are explained as external, temporary, and specific. For counsellors, an optimistic explanatory style creates positive expectancy judgments about the possibilities and opportunities for successful client outcomes. In this research study, we explored the explanatory styles expressed in 400 events (200 good events and 200 bad events) extracted from 38,013 writing samples of first year and final year graduate level counsellors in training. Across the three optimism dimensions and within good and bad events, there was one occurrence of a positive relationship between counsellor training time and the amount of expressed optimism. The implications of this study include the need to cultivate optimistic explanatory styles of counsellors in training and practicing counsellors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".