Two Old Women: Occupation of Resolving Life Crisis in Old Age
Bibliographic record
Abstract
As a person ages and accumulates life experience, the person becomes a unique occupational being. While people develop their own life styles, repeating and recreating life continuity while meeting life’s events, their personalities and strategies tend to become strong, sometimes rigid. The presentation, “Two old women”, is titled after an Alaskan legend of Inuit women (Wallis, 1993) who experienced a life crisis after being left by their tribe in a severe winter and instead of accepting death, they decided to survive. They chased rabbits, collected twigs and endured coldness and fatigue. Finally, the two old women returned to their tribe with new resilience and with a different social position than before. This presentation is about two old women living in contemporary Japanese society who suffered from life crisis brought on by health problems. We study their life experience to investigate the occupation of resolving life crises in old age. The data used in this research was originally collected for two different studies regarding elderly person‚s occupation. Our methods were open-ended interview and participant observation. One woman, Yuki, was anxious about her future when she recognized her memory problems. She feared causing a stove fire at home and decided to move into an apartment with care service. In the new place, Yuki developed social relationships, but maintained close relationship with her family living separately. She continued enjoying hanging around with her old friends, who shared her life meanings in their old age. The other woman, Hana, because of a stroke, gave up her life and close relationships with her loved ones. Occupational therapy intervention guided her to engagement in occupations meaningful to her and her social experience. Hana recreated a new life and recovered relationships with her family and people around her. Yuki and Hana each resolved a life crisis in old age and went on to live a „meaningful existence„ (Jackson, 1996, p.339). Engaging in familiar occupations, they have recaptured disappearing or lost life continuity. In this presentation, showing similarities and difference between the two women, we analyze the occupation of resolving life crises in old age, from phenomenological perspectives.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".