<i>Seeing the light</i> versus <i>being in the dark:</i> parent, child, and service providers’ use of metaphors to express system complexity, therapy engagement, and personal experiences of adaptation
Bibliographic record
Abstract
PURPOSE: To describe parent, child, and service providers' use of metaphors to communicate the meaning of participation in life and therapy engagement in the field of childhood disability. METHODS: Metaphors concerning participation and engagement were extracted from 59 qualitative articles recommended by a group of experts in pediatric rehabilitation. A systematic process of metaphor analysis was used, involving identification of source and target domains, categorization into target-source groupings, and interpretation. RESULTS: 209 metaphors were identified and categorized into seven target-source groupings. These seven groupings reflected environmental, interpersonal, and personal domains of experience: (a) the service system and life context, (b) the interpersonal therapy context, and (c) personal aspects. Together, the groupings expressed experiences concerning service system complexity, therapy engagement, and personal experiences of adaptation. Speakers used several metaphor dichotomies to express different experiences (e.g., open vs closed doors to opportunities). CONCLUSIONS: When service providers pay attention to clients' use of metaphors, this can lead to a deeper, more evocative understanding of the meaning of their participation and engagement experiences. Service providers can use metaphors generated by clients to communicate their understanding to clients, thereby creating a common ground for collaboration and assisting clients to interpret their experiences in different ways.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".