Developing process sensitivity: Reply to Wilcox (2024) and Boswell (2024).
Bibliographic record
Abstract
Wilcox (2024) and Boswell (2024) make a number of important observations about facilitating process sensitivity training, and here, we respond to those suggestions. We postulate that cultivating process sensitivity is complementary, not antithetical, to traditional training in viewing therapy from a theoretical lens, and thus, can serve to enhance, rather than replace one's existing psychotherapy skills. Moreover, we argue that seeing the impact of process adjustments in real time can be a significant motivator for training in process sensitivity since the benefits are more immediately obvious. We further argue that the field can be more thoughtful about the use of simulations in training and the emerging interactive training platforms using video stimuli, since they facilitate exposure to clinical situations in a safe manner. Finally, while learning to identify process markers can play a valuable role in optimizing the timing of interventions, we argue that this pales in comparison to the value of process sensitization as a means of attending to outcome information in the moment ("little outcome"). If successful, this opens up the possibility of developing expertise in psychotherapy, which hitherto was considered not possible. However, these propositions require rigorous testing in studies on training and supervision. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".