“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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".