The Analyst’s Generous Involvement: Recognition and the “Tension of Tenderness”
Bibliographic record
Abstract
I define the analyst’s generous involvement as inherent to human encounter and a necessary element of therapeutic process. When the analyst’s generous involvement goes missing, it can be read as a sign of disengagement and disconnection. Using as metaphor H. S. Sullivan’s concept of the “tension of tenderness,” I argue that the analyst’s recognition of a need or affect state in the patient evokes an internal tug constituting the analyst’s need to provide for what has been recognized. I elaborate on what the analyst’s generous involvement is, and what it is not, including countertransference pitfalls and corruptions that may masquerade as generosity. I engage a relational conversation with the radical ethical ideas of Emmanuel Levinas. An extended clinical vignette illustrates the challenges and conflicts entailed in the analyst’s finding an analytically useful form of expressing the tug of generous involvement in the immediate moment.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.039 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.005 | 0.010 |
| 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".