Co-living as a choice for independent retired women: Hope for social transformation
Bibliographic record
Abstract
In this paper we present the results of a study of a successful co-living project for independent retired women.As our societies are increasingly concerned with sustainable living, we see that aging populations are often overlooked.Yet there is going to be an increase on these populations.During COVID in the Canadian context, some grave concerns were raised around retirement homes.For instance, by not allowing visitors the aging, already feeling lonely, were further cut-off from needed family social contact.Living close together in their common space increased major health issues with higher percentages of death.There were also increasing numbers of fires with significant numbers of deaths.Moreover, retirement homes are costly.With increasing financial constraints in many countries, older people feel financial burdens and there is a need to reconsider the conditions in which older people are finding themselves.Spontaneous groupings and living together experiments have generally failed.Even friends living in a house together usually experience issues after a few years.We investigated the successful Babayaga House co-living model in Paris that has been successful for over 12 years to uncover characteristics that are favorable for such projects to continue to strive.Through the analysis of journals and other documents found in the public domain we uncovered desirable attitudes and qualities to help identify social factors that can lead to such a sustainable governance model.The method used was qualitative.To understand the complexity of the underpinnings of the system we recruited volunteers to make regular journal entries over six months.We also carried out a literature search to identify recognized questionnaire models that could be useful to map out the criteria for our study.The journal entries and additional documentation from the public domain were analyzed for emergent themes.Then these were paired with relevant entries from the existing well-being questionnaires identified in the literature search.We discuss our findings and present an articulation of the main concepts behind the successful functioning of the French model, also taking into account some of the major issues identified.Among major themes uncovered were autonomy, collaboration, accountability, the need for a number of positive traits like positive emotions, positive relationships and positive thinking with a total of 33 themes.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.014 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".