Unpacking and Keeping it Packed: Two Forms of Therapist Responsivity
Bibliographic record
Abstract
The terms “unpacking” and “keeping it packed” are used here to distinguish two practices of systemically informed therapy. Human beings exist and operate in an array of experiential constraints that serve to stabilize but also to limit the dimensions of a person's process of living. Unpacking is a form of interaction in which therapist and client collaborate to generate more possibilities by identifying, opening up, breaking up, and making distinctions within existing constraints. With keeping it packed, the therapist facilitates a different form of relationship between the client and his/her experience of those phenomena that elude easy description yet are directly sensed and felt. This article seeks to define these terms and provide examples of and an argument for their use in the context of systemically informed therapy.
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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 | 0.020 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.057 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".