Storytelling and the interpretation of meaning in qualitative research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: This paper reviews literature on narrative analysis and illustrates the meaning-making function of stories of chronic illness through analysis and discussion of two case studies from a study of acute episodes of chronic obstructive pulmonary disease (COPD). BACKGROUND: Individuals living with COPD experience acute exacerbations characterized by extreme dyspnea, but there has been little research to provide understanding of these events from the perspectives of individuals with COPD, family caregivers, and nurses. Narrative analysis -- considered in the context of the aims of qualitative research -- illuminates how these people make sense of acute exacerbation events by telling stories. DESIGN AND METHODS: In an ethnographic study, 10 patient-family nurse units in two Canadian general hospitals participated in interviews concerning acute episodes of COPD. Narrative analysis enabled identification of several story forms and their functions. RESULTS: Examples were found of a story told twice with different meanings, and of a patient's 'death story' used to communicate distrust of the nurse's ability to recognize the seriousness of distress and implications for its potential course. These examples are presented, and interpreted with respect to issues of meaning. CONCLUSIONS: The analysis indicates that stories told by patients in the context of nurse-client interactions inform understanding of the individual's acute exacerbation events beyond the biophysical.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it