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Record W7043687229

SWAHN Southwestern Academic Health Network Conference 2017 : the Patient Voice & Experience in Southwestern Ontario

2017· other· en· W7043687229 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2017
Typeother
Languageen
FieldMaterials Science
TopicX-ray Diffraction in Crystallography
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipPresentation (obstetrics)Session (web analytics)NarrativeIndigenousHealth carePatient experienceSimulated patientDocumentation
DOInot available

Abstract

fetched live from OpenAlex

The conference, held at Western University in London, Ontario, was a full-day event that included presentations based on its theme: The Patient Voice and Experience in Southwestern Ontario. The day began with a two-part presentation featuring Health Quality Ontario’s patient partnership framework, delivered by Jennifer Schipper, Health Quality Ontario’s Chief of Communication and Patient Engagement. Dr. Gillian Kernaghan, President and CEO of St. Joseph’s Health Care London (and Co-Chair of SWAHN) then shared her organization’s care partnership that has involved the contributions of patients, residents, families, and caregivers.\nOther presentations included a personal story shared by Mr. Wayne Kristoff who was engaged as a patient in a research study for diabetics at the Lawson Health Research Institute. This was followed by Dr. Shannon Arntfield’s presentation on the value that practicing narrative medicine offers to both health care providers and their patients. The morning session concluded with a special theatrical production that explored the Indigenous patient experience.\nIn the afternoon, breakout sessions on patient partnerships and the Indigenous patient experience were held, sparking discussion among participants. Following the conference, various themes were identified based on an analysis of the various breakout group discussion notes and participant evaluations. The following key learning points were identified by participants both during the group discussions and through the conference evaluation forms.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.780
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0050.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.002

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 head0.151
GPT teacher head0.348
Teacher spread0.197 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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