Bibliographic record
Abstract
RATIONALE: A troubling phenomenon for caregivers of elderly parents is their tendency to tell the same stories over and over. Repeated storytelling raises concerns about cognitive decline and memory loss and is often considered a disturbing harbinger of the possible onset of dementia. PURPOSE: This research aims to show that repeatedly told stories are important vehicles for intergenerational transmission of values. METHODS: Using a narrative inquiry approach, this research involved structured interviews with middle-aged adult children, asking them to tell us the stories they felt they were hearing or had heard repeatedly from their aging parent. Interviews were taped and transcribed, then coded for temporality, purpose and content. RESULTS: Based on 126 stories told to 13 participants, it can be confirmed that there are approximately ten stories that older parents repeatedly tell to their adult children, mostly about experiences in their teens and twenties. The majority of the stories are told for the purpose of consolidating the elder's identity or sharing wisdom with the adult child. Key themes in the stories include seeking a better life, youthful fun, upholding standards, sticking together and doing what's right. These themes reflect the significant events and prevailing values of the early to mid-twentieth century. CONCLUSION: This research offers a more constructive way for caregivers to hear the repeated stories told by their aging parents and to offer their loved one the gift of knowing they have been seen and heard.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".