“A Day in the Life”: A simulated experience
Bibliographic record
Abstract
An experiential learning activity titled, “A Day in the Life” was implemented with nineteen baccalaureate nursing students in order to achieve a holistic understanding of the challenges faced by persons living with Schizophrenia and a physical disability, such as a fracture in an upper extremity or a visual impairment. The role play simulation required that students interact with public transportation and community resources, while assuming the role of a person with Schizophrenia and a physical disability. Using a qualitative descriptive methodology, reflective journals, aesthetic expressions, and post conference discussions about “A Day in the Life” were reviewed and analyzed by the authors. Two major themes were identified from the journal data: Changed Person, and Eye-Opening. Exemplars illustrating each theme are provided in the manuscript. Based on the results of this study, the authors believe that the role play simulation, “A Day in the Life” was effective in helping students to achieve a holistic understanding of the challenges faced by persons living with Schizophrenia and a physical disability. Further use of this experiential learning activity, with multi-method evaluation, along with short and long term follow-up is recommended.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".