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Record W4378373311 · doi:10.1177/1035719x231179984

Advancing an ethical imperative for collaborative approaches to evaluation with low incidence and underserved communities: Insights from a DeafBlind Support Services pilot program evaluation

2023· article· en· W4378373311 on OpenAlexaffabout
Vannesa Joly, Colleen McClure, Cheryl Poth, Navida Bachan, R McCarthy, C. Stephen Redhead, Jacqueline Pei

Bibliographic record

VenueEvaluation Journal of Australasia · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTransformative learningVocational educationRecreationService (business)Participatory evaluationPsychologyPublic relationsMedical educationSociologyPolitical scienceMedicinePedagogyBusiness

Abstract

fetched live from OpenAlex

This practice article advances an ethical imperative for guiding collaborative approaches to evaluation with low incidence and underserved communities. We describe our evaluation processes for building transformative partnerships during a DeafBlind Support Services pilot program evaluation in Western Canada using collaborative approaches to evaluation. This program was designed to enable adults living with dual sensory loss to experience self-determined activities in the community that enhance resilience and belonging. Key features involve specialised Support Service Providers who assist DeafBlind community members with accessing and participating in essential community services and social, vocational, educational, and recreational activities. In presenting our co-generated evaluation insights, we advance an ethical imperative describing philosophical foundations, pragmatic actions, and political leadership for implementation of collaborative approaches to evaluation with a low incidence and underserved community.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptno category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
grokno category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: yes
Qualitativehigh
opusno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualmedium
models splitAgreement compares identical category sets and study designs across arms.

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)0.038
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.315
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0380.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0000.001
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 head0.466
GPT teacher head0.509
Teacher spread0.042 · 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

Labeled directly by 3 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative · Theoretical or conceptual
Domainnot available
GenreMethods · Commentary

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

Citations2
Published2023
Admission routes2
Has abstractyes

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