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Record W4307260408 · doi:10.5206/ijoh.2022.2.14485

COVID-19 Vaccination and Hesitancy among People Experiencing Homelessness in Sacramento, California

2022· article· en· W4307260408 on OpenAlexvenueno aff
Ryan Finnigan

Bibliographic record

VenueInternational Journal on Homelessness · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersUniversity of California, Davis
KeywordsVaccinationOutreachCoronavirus disease 2019 (COVID-19)PopulationMedicineHealth careEnvironmental healthGerontologyFamily medicineDiseasePolitical scienceInfectious disease (medical specialty)Immunology

Abstract

fetched live from OpenAlex

Severe illness and mortality from coronavirus disease 2019 (COVID-19) are especially pronounced threats for people experiencing homelessness. COVID-19 vaccination access is correspondingly urgent for this population. Advocates, healthcare providers, and homelessness service providers have been conducting substantial vaccination outreach in places around the world. Systematic empirical research should support and inform these efforts. This study estimates COVID-19 vaccination rates and reasons for hesitancy among people experiencing homelessness in Sacramento, California, as of late September and early October 2021. Survey data (N = 283) estimate that 58% of people experiencing homelessness in Sacramento were fully vaccinated and 65% were at least partially vaccinated, but these estimates are likely upper bounds for the true population rates. Many unvaccinated people still planned to receive the vaccine, and concerns about safety and side effects were the most common reasons for hesitancy. Vaccination was more common for people using homelessness services at higher levels, but even frequent visits to drop-in centers were associated with higher vaccination rates among unsheltered people. This group was especially likely to have been vaccinated through outreach efforts, like pop-up vaccination clinics and street medicine teams. The study’s results hopefully inform ongoing vaccination efforts and contribute to a growing empirical literature on this urgent topic.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.034
GPT teacher head0.391
Teacher spread0.357 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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