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Record W3135574149 · doi:10.3390/ijerph18052297

“They Are Worth Their Weight in Gold”: Families and Clinicians’ Perspectives on the Role of First Nations Health Workers in Paediatric Burn Care in Australia

2021· article· en· W3135574149 on OpenAlexaboutno aff
Julieann Coombes, Sarah Fraser, Kate Hunter, Rebecca Ivers, A.J.A. Holland, Julian Grant, Tamara Mackean

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2021
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMultidisciplinary approachOccupational safety and healthMultidisciplinary teamMedicineHealth careWork (physics)NursingSuicide preventionInjury preventionPoison controlHuman factors and ergonomicsPsychologyEnvironmental healthPolitical science

Abstract

fetched live from OpenAlex

Burns affect Australia's First Nations children more than other Australian children, they also experience longer lengths of stay in tertiary burns units and face barriers in accessing burn aftercare treatment. Data sets from two studies were combined whereby 19 families, 11 First Nations Health Worker (FNHW) and 56 multidisciplinary burn team members from across Australia described the actual or perceived role of FNHW in multidisciplinary burn care. Data highlighted similarities between the actual role of FNHW as described by families and as described by FNHW such as enabling cultural safety and advocacy. In contrast, a disconnect between the actual experience of First Nations families and health workers and that as perceived by multidisciplinary burn team members was evident. More work is needed to understand the impact of this disconnect and how to address it.

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)0.021
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.050
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0150.011
Scholarly communication0.0060.007
Open science0.0020.007
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0030.000

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 head0.375
Teacher spread0.318 · 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 designQualitative
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

Citations28
Published2021
Admission routes1
Has abstractyes

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