“Stay at Home” Inhabiting Public Space During the COVID-19 Pandemic: Social Productions of Care with People Experiencing Homelessness in the Autonomous City of Buenos Aires
Bibliographic record
Abstract
Living on the streets is a global public health problem that is institutionalized in different local contexts. After the coronavirus disease of 2019 (COVID-19) pandemic was declared in the Autonomous City of Buenos Aires (CABA), the care coverage for Persons Experiencing Homelessness (PEH) was reduced to a few social and community organizations. This paper presents the preliminary results of participatory research using a network research design. We worked with referents from community organizations and PEH, combining synchronous and asynchronous actions through digital media and face-to-face strategies. The COVID-19 pandemic scenario generates challenges for interventions with PEH by revaluating narratives of risk. The relationship between self-care and collective care is problematized in the responses generated by civil society to ensure continuity of care in this socio-health emergency.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".