MétaCan
Menu
Back to cohort

Advance Care Planning: A Community Engagement Value Based Approach

2011· article· en· W2151549736 on OpenAlexaffabout
Carol Robinson, Tom Fulton, D. N. Collins, B Lacasse, Alan Wren, Laura J. Myers, Judy Nicol, Jennifer Thompson

Bibliographic record

VenueBMJ Supportive & Palliative Care · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsInterior HealthUniversity of British Columbia
Fundersnot available
KeywordsUnderpinningNorm (philosophy)Value (mathematics)Public relationsProcess (computing)Health careCommunity engagementKnowledge managementPsychologyPolitical scienceProcess managementMedical educationSociologyMedicineComputer scienceBusinessEngineering

Abstract

fetched live from OpenAlex

This workshop focuses on the design and ongoing implementation of an innovative advance care planning (ACP) initiative in one Canadian Health Authority. The initiative took a values based, community engagement approach to developing an ACP program in two communities. Developmental evaluation systematically informs the emerging programs. The initiative is in its second year and successes to date include: a shift in the relationship between the health authority and participating communities in response to a new way of ‘doing business’ where change is not mandated from the ‘top down’ but emerges ‘in the middle’ through active collaborative engagement; capacity development within both the health authority organizational team and the participating communities; a community specific vision of ACP that is broader than health care decision making; and, a comprehensive education program for ACP facilitators. This innovative approach has been challenging to enact in a system where a traditional policy based orientation to program development and outcomes based evaluation are the norm. Instead, success has been determined via real time decision making that aligns with the values framework underpinning the project. Multiple course corrections have occurred such as adopting developmental evaluation and moving away from an evaluative logic model. The responsive, values based process will be discussed, strengths and challenges identified and successes highlighted.

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)0.003
metaresearch head score (Gemma)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.805
GPT teacher head0.669
Teacher spread0.137 · 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 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

Citations0
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueBMJ Supportive & Palliative CareSame topicHealth Policy Implementation ScienceFrench-language works237,207