The “Recreated Experiences” Approach: Exploring the Experiences of Persons Previously Excluded in Research
Bibliographic record
Abstract
Individuals with profound motor, communication, and/or cognitive impairments may face difficulties describing subjective or experiential information through (i) speech, (ii) writing using a pencil and paper, and (iii) typing using a standard computer keyboard. Although patient-reported outcome measures and patient-reported experience measures can capture information about this group through proxy-report, we cannot solely rely on the responses of a single proxy for experiential information. Research methods to understand the experiences of individuals with profound motor, communication and cognitive impairments are not well defined in the literature. Purpose: To provide guidance to disability researchers on how to explore the subjective and personal experiences, of individuals with profound, motor, communication, and/or cognitive impairments. Three axes are proposed as important to the structure of the “recreated experiences” method: (i) informants, (ii) data collection methods, and (iii) analyses and reflexivity. Different types of information can be gained by involving different informant groups in research about the central person’s experience. Primary guardians can provide information about interpreting central persons’ indicators of expression and broad assessments of their personal life. Other adults can provide insight relative to the central person’s capacities outside of the primary guardian-central person dyad. Peers can provide insight about personal characteristics (i.e., personality traits). Utilizing different data collection methods can foster manifest and latent content to emerge. Analyses and reflexivity which involve diverse perspectives are essential to ensure findings are grounded in lived experience and professional lenses. The method highlights the importance of furthering research to understand the experiences of individuals who cannot traditionally self-express, which may influence possibilities for enhancing care, participation opportunities, and overall well-being.
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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 | 0.038 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.008 | 0.029 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.003 | 0.005 |
| 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".