MétaCan
Menu
Back to cohort
Record W4281559548 · doi:10.5206/ijoh.2022.2.13727

“We Don't Get Sick we're Invisible”: The Policy Aimed at Homeless People in the City of São Paulo and its Effects During the COVID-19 Pandemic

2022· article· en· W4281559548 on OpenAlexvenueno aff
Morgana G. Martins Krieger, Caio Coradi Momesso, Giordano Magri

Bibliographic record

VenueInternational Journal on Homelessness · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado de São PauloFundação Getulio Vargas
KeywordsPandemicPopulationVulnerability (computing)Government (linguistics)CensusState (computer science)Economic growthPublic policyPolitical scienceCoronavirus disease 2019 (COVID-19)SociologyDevelopment economicsGeographyPublic administrationMedicineDemographyEconomicsDiseaseComputer security

Abstract

fetched live from OpenAlex

The 2019 census identified that São Paulo had a homeless population of 24,344 people, a situation potentially worsened due to the crisis generated by the COVID-19 pandemic in 2020. Since the 1990s, a regulatory framework that obliges the municipal Executive Branch to serve this population has been strengthened, including instruments for participation. This article aims to conduct an analysis of this policy, verifying its application through the COVID-19 pandemic. Understanding the underlying complexity of this population’s living conditions, the authors adopted a vulnerability perspective to develop such an analysis, focusing on institutional vulnerability. Based on this discussion, this study approached the following question: How are the state of São Paulo’s actions related to the homeless population’s vulnerability, and what are the consequences of this condition during the COVID-19 pandemic? Based on qualitative secondary data, this article is presented as a result of the historical survey of the policy to protect the homeless population and the interaction between this population and the State. This article also reviews different forms of vulnerabilities to which the São Paulo homeless population is exposed, and the actions implemented by the government during the pandemic. As a contribution, the authors raise the negative and positive impacts of the state’s actions on the living conditions of this population, adding to the literature on institutional vulnerabilities and directing an investigation of the organizational elements of the public sector that may be associated with these impacts. No censo de 2019, identificou-se que São Paulo tinha uma população em situação de rua de 24.344 pessoas, situação potencialmente agravada pela crise gerada pela pandemia de COVID-19 a partir de 2020. Desde a década de 1990, um marco regulatório que obriga o Poder Executivo municipal a atender este público tem sido fortalecido, abrangendo inclusive instrumentos de participação. Este artigo tem por objetivo tecer uma análise dessa política, verificando sua aplicação no momento singular que é a pandemia de COVID-19. Compreendendo a complexidade subjacente às condições de vida deste público, adotamos a lente de vulnerabilidades para desenvolver tal análise, com foco especial em vulnerabilidade institucional. A partir dessa discussão, colocamos a seguinte questão: como as ações estatais se relacionam com a condição de vulnerabilidade da população em situação de rua e quais os desdobramentos de tal condição durante a pandemia da COVID-19? Construído qualitativamente a partir de dados secundários, este artigo apresenta como resultados o levantamento histórico da política de proteção à população em situação de rua e os modos de interação entre esta população e o Estado, mais especificamente, o de São Paulo; e as diferentes formas de vulnerabilidades às quais essa população está exposta e as ações implementadas durante a pandemia. Como contribuições, trazemos os impactos negativos e positivos da ação estatal na condição de vida dessa população, agregando à literatura das vulnerabilidades institucionais, além de direcionar uma investigação para os elementos organizacionais do setor público que podem estar associados a esses impactos.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.407
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal on HomelessnessSame topicHomelessness and Social IssuesFrench-language works237,207