MétaCan
Menu
Back to cohort
Record W2056046026 · doi:10.1177/1476750305058487

Community mapping as a research tool with youth

2005· article· en· W2056046026 on OpenAlexaffabout
Jackie Amsden, Rob VanWynsberghe

Bibliographic record

VenueAction Research · 2005
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of British ColumbiaOntario Centre of Excellence for Child and Youth Mental Health
Fundersnot available
KeywordsParticipatory action researchParticipatory evaluationAction researchProcess (computing)Community-based participatory researchCitizen journalismField (mathematics)Action (physics)SociologyData collectionPublic relationsComputer sciencePolitical sciencePedagogyWorld Wide WebSocial science

Abstract

fetched live from OpenAlex

This article provides a detailed description of the in-field experience of using community mapping as a participatory action research tool with youth. It describes a case study, the Youth Friendly Health Services project (YFHS project), in which a team of Vancouver youth carried out a participatory evaluation of health clinics by mapping out criteria for evaluation and then creating an evaluation tool based on the maps that were created. Community mapping proved to be an inclusive and appropriate tool to engage youth perspectives. The major challenges faced in the process were in determining how to represent and act upon the findings of the mapping process. Their experience suggests that while such innovative data collection tools such as community mapping can successfully engage youth, not just as participants, but as facilitators of research, they must be accompanied by equally creative and innovative approaches to formulating research results and outcomes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.048
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0110.009
Scholarly communication0.0090.009
Open science0.0030.013
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.829
GPT teacher head0.680
Teacher spread0.149 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations159
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueAction ResearchSame topicCommunity Health and DevelopmentFrench-language works237,207