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Record W4318977084 · doi:10.35844/001c.66191

Combining the World Café and the Deliberative Democratic Evaluation: A Win-Win Strategy

2023· article· en· W4318977084 on OpenAlexaffabout
Kristelle Alunni‐Menichini, Karine Bertrand, Astrid Brousselle

Bibliographic record

VenueJournal of Participatory Research Methods · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of VictoriaUniversité de SherbrookeMcGill University
Fundersnot available
KeywordsDeliberationThematic analysisDemocracyInclusion (mineral)Relevance (law)Public relationsPsychologyDeliberative democracyPolitical scienceDescriptive statisticsQualitative researchSociologySocial psychologySocial science

Abstract

fetched live from OpenAlex

The current emergency response for substance users experiencing homelessness is not adapted to their needs. This has led to the revolving door phenomenon and to issues of collaboration between involved organizations. This study aims to demonstrate the relevance from the participants’ perspective of: 1) the World Café; 2) the deliberative democratic evaluation; and 3) combining these two methods as part of a qualitative study aimed at improving emergency response to substance users experiencing homelessness in Montreal. Thirty-four people participated in an intersectoral World Café guided by the principles of deliberative democratic evaluation. Twenty-three participants responded to a questionnaire regarding their satisfaction, effects of their participation, and adherence to the principles of deliberative democratic evaluation (inclusion, dialogue, and deliberation). We performed descriptive statistics and a thematic content analysis. Ultimately, the respondents were satisfied with the activity and several said they gained new knowledge and improved their network. Roughly half of the participants shared that their participation influenced their representations and their future practices. Our findings suggest that combining deliberative democratic evaluation and World Café is relevant to providing rich qualitative data, gaining systemic insight, and having an impact on our communities (e.g., improving intersectoral collaboration, professional’ attitudes and practices).

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)0.114
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1140.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.795
GPT teacher head0.732
Teacher spread0.064 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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