Community wellbeing: The impacts of inequality, racism and environment on a Brazilian coastal slum
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article applies the 3-dimensional wellbeing lens (based on material, relational and subjective dimensions of wellbeing) to examine the factors that affect wellbeing in a slum community (Vila dos Pescadores, in the city of Cubatão, Southeast Brazil). This wellbeing framework proves useful in understanding how community wellbeing is impacted by several negative factors: the perceptions of slums, the presence of systemic racism and growing inequality, and a range of environmental impacts arising from industrial and urban pollution, and environmental disasters. Within this mix of environmental and social impacts are links between poverty and exposure to environmental hazards, and effects of environmental racism. On the positive side, these threats to community wellbeing are countered to some extent through targeted measures carried out by the community association and its partnerships, and through beneficial governmental policy measures. Together, these responses help to reduce the detrimental effects of an unhealthy and dangerous environment, and of social concerns such as exclusion, poverty, urbanization and inequality. Key to the success of response measures are the contributions of the community leadership to improve the wellbeing of slum-dwellers by counterbalancing the effects of racism and social inequality, and implementing social programs and community facilities, thereby filling the gaps created by a lack of state support to slums. These actions illustrate what impoverished communities can do to improve livelihoods and wellbeing, and to combat problems such as environmental degradation and racial discrimination. This article also draws lessons for improving wellbeing analysis, particularly in slum communities, through a greater focus on (1) collective wellbeing and a community-focused view of wellbeing, (2) impacts of racism and inequality, and (3) interactions between community wellbeing and community leadership.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it