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Record W4220953985 · doi:10.1093/jbcr/irac012.191

563 Fire safety in homeless encampments

2022· article· en· W4220953985 on OpenAlexaff
Sarah Rehou, Greg Cook, Nathan Doucet, Marc G. Jeschke

Bibliographic record

VenueJournal of Burn Care & Research · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsTD Bank GroupHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsOutreachGeneral partnershipMedicineFire safetyHarmOccupational safety and healthPublic relationsPsychologyBusinessSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Abstract Introduction It is well known that people experiencing homelessness are at a greater risk for burn injury. Our burn centre saw an increase in admissions of homeless individuals during the pandemic. Typically, we partner with our hospital’s communications staff to share burn prevention public service announcements. But our usual method of broadcasting information through media like newspapers, blog posts, Facebook, or Instagram was not necessarily going to reach people sleeping rough. This report describes the development of a partnership between a burn centre, outreach workers, and people with lived experience of homelessness to improve fire safety in encampments. Methods Our goal was to create a Fire Safety Manual and hold Fire Safety Training Sessions. We conducted surveys that asked encampment residents questions like, “What do you use fires for?” “What fire hazards do you see at encampments?” and “How do you think fires could best be prevented?”. We used the results of this survey to guide the training manual and held workshops to engage encampment residents and incorporate feedback into the manual. Results The manual uses harm reductions strategies and focuses on real-life situations encountered by folks living outdoors—the manual outlines how to safely start a fire and what to do if a fire occurs. The reality is that people are trying to survive freezing winters while sleeping outside; this means that some safety standards are not possible, and the guide had to reflect that. For example, we practiced fire escape plans during training sessions and had to think about obstacles like tents with only one way out. A solution was to keep a utility knife inside and outside the tent in case one had to cut through to escape or free someone. An encampment resident suggested hiding the knives so they would not be used as weapons. We purchased fire extinguishers, fire blankets, and first aid kits that we distributed during training. Conclusions Education is critical to prevent burn injuries. Burn centre staff may be experts on burn prevention, but we are not experts on surviving outside. We have to be accountable to this community. This means listening, building trust, and partnering with people living outdoors. People who did training sessions were empowered to start fire brigades in their encampments. Crucial concepts are to meet people where they are and always to include people with lived experience: “Nothing about us without us.”

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.124
GPT teacher head0.521
Teacher spread0.397 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations7
Published2022
Admission routes1
Has abstractyes

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