Achieving ‘Good Health and Well-Being’ for Women in Diverse Socio-Economic Neighbourhoods
Bibliographic record
Abstract
Designing a place for women facing daily hardships often demands a distinct set of interventions that often bring unique challenges to designers. The Northside neighborhood is a poor and racially tensioned neighborhood with a lack of opportunity and social support. Many families in this neighborhood experiencing economic difficulties rising from such inequality and inadequate provision of opportunity, have raised concerns for no or limited access to basic necessities such as housing and healthcare. Particularly women in the Northside neighborhood raised their concerns about not a having socially and culturally safe environment in which they can engage in wellness activities (Stasya Erickson and Jonathan Logan, Personal Communication, June 18, 2018). Having daily challenges with childcare, financial hardship, accessibility, communication, cultural traditions that prevent them from taking care of their mental and physical wellness, these women do not have the luxury to concern about their health and wellbeing. Besides, conventional health facilities have been designed rather emphasizing the functional delivery of the space, which often lacked or unsuited to satisfy the psychological or social needs. This paper discusses the processes and results of three community design charrettes conducted to gather information on the need for women's fitness center with an aim to promote holistic means of wellness. The three design charrettes were organized with a) residents from the Northside community (n=15); b) local organizational stakeholders and community leaders (n=7), and c) potential wellness center partners (n=2). In conjunction with the design charrettes, an alternative market study survey (n=108) was conducted to learn about people’s opinions and views on the community’s primary interests and the needs for the women-focused health system in the Northside neighborhood. Both charrettes and survey discovered that women’s immense needs for childcare, sense of community, security, and privacy can be pursued through their participation to participate in the wellness activities. This research posits that design based on community’s voices would help designers, educators, and policymakers to produce a realistic and impactful design that responds to the needs of women in diverse socio-economic neighborhoods.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".