MAKING CAPE TOWN AN AGE-FRIENDLY CITY: AN EXPLORATORY STUDY
Bibliographic record
Abstract
Living environments characterized by infrastructural and developmental deficits hamper older citizens’ integration in society for an active and healthy life. This study investigated older citizens’ experience and perceptions of the “age friendliness” of their communities in the City of Cape Town. The methodology based on the Vancouver Protocol 2006 and advocated by the WHO’s project on “Age friendly Cities,” was used. Low-income suburbs of Cape Town were selected and qualitative research methods (ten focus groups with members and interviews with managers of service centres) were used to collect and analyse the data. A sample 97 participants, mean age 70 years (range 54–83) were recruited. Eight domains constructed for the assessment of age friendliness were: physical environment, transport, housing, social participation, respect and social inclusion, civic participation, community support and health services, and communication and information. Barriers to social inclusion and participation were: Government restriction in income generating activities for social pensioners; features of the physical environment particularly uneven, poorly lit and unsafe sidewalks; short timing at traffic light for pedestrian-crossings; public transport services that were inaccessible to commuters with disability and younger commuters not offering their seats to them. Ageistic attitudes of personnel and the unfriendly services at public healthcare facilities were widely reported. Services and support from religious and other community agencies and travel concessions from government were valued. Lack of exposure and inability to access pertinent electronic information was a concern for a large number. A productive and inclusive society calls for relevant stakeholders to address the concerns.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".