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Record W6891577860 · doi:10.4224/40002815

CSC smudging toxicity: literature review

2022· report· en· W6891577860 on OpenAlexaffvenueabout

Bibliographic record

VenueNPARC · 2022
Typereport
Languageen
Field
Topic
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSmokeDirectiveHuman healthTobacco smokeService (business)

Abstract

fetched live from OpenAlex

Smudging activities are conducted in correctional facilities by inmates as part of a cultural ritual. Correctional Service Canada (CSC) Commissioner’s Directive (CD) 702: Aboriginal Offenders1 defines smudging as the act of burning traditional medicines (e.g. sweet grass, sage, cedar or tobacco) to pray and purify oneself or physical space. CSC Standing Order (SO) 259: Millhaven Institution- Accommodation of Spiritual Practices2 further indicates that various types of tobacco including commercial tobacco may be used in circumstance. A smudge is smoke producing/smouldering of a smudge material. In the previous study conducted for the CSC in 20183 , the NRC (National Research Council Canada) tested three selected smudging materials to investigate how much smoke is generated from the smudging materials and how smoke detectors respond to the smudging. The previous study reported that the smudging sources produced large amounts of smoke although a limited amount of the smudging sources was burned using a small heat source (hot plate) in a test room. The level of smoke obscuration measured from the smudging sources was significantly higher than that resulted from the same amount of other smouldering sources (e.g. pieces of blanket, bed sheet and mattresses) tested in the room. The CSC has requested a study to assess the effects of exposure to smudging smoke/effluents on human health. As an initial step, NRC conducted a literature review in collaboration with FireTox, LLC. to understand the types of effluents produced from smudging and their health hazards to inmates and correctional facility staff. A full report on the literature review is attached in Appendix A. The following sections provide a summary of the literature review report.

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)0.003
metaresearch head score (Gemma)0.012
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: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0130.012
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.039
GPT teacher head0.326
Teacher spread0.286 · 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
GenreReview

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

Citations0
Published2022
Admission routes3
Has abstractyes

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