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Record W4387197460 · doi:10.1007/978-3-031-40379-8_20

Introducing the Downtown Eastside Community Research Ethics Workshop: Notes on a Process for Community Ethics Review

2023· book-chapter· en· W4387197460 on OpenAlexaff
Scott D. Neufeld, Jule Chapman, Nicolas D. Leech-Crier, Samona Marsh, Jim McLeod

Bibliographic record

VenuePhilosophy and medicine · 2023
Typebook-chapter
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsBC Mental Health & Substance Use ServicesPositive Living Society of British ColumbiaVancouver Coastal HealthBrock University
Fundersnot available
KeywordsEngineering ethicsNursing ethicsResearch ethicsDowntownCommunity buildingInformation ethicsSociologyProcess (computing)Public relationsPolitical scienceMedicineEngineeringComputer science

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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
gemmaResearch integrity
Domain: not available · Genre: Other
About the Canadian research system: yes · About a Canadian topic: yes
Qualitativelow
gptMetaresearchResearch integrity
Domain: Methods · Genre: Commentary
About the Canadian research system: yes · About a Canadian topic: yes
Qualitativemedium
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)0.171
metaresearch head score (Gemma)0.514
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.581
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1710.514
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0050.007
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0030.146
Insufficient payload (model declined to judge)0.0000.000

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 head0.901
GPT teacher head0.661
Teacher spread0.240 · 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 2 models reading the full record.

Research integrityMetaresearch

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

Study designQualitative
DomainMethods
GenreOther · 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

Citations1
Published2023
Admission routes1
Has abstractno

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