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An Autoethnographic Account of Experiences with a Community-Based Participatory Research Project in Canada

2018· article· en· W2903793900 on OpenAlexaffabout
Martha Dowsley, Frederico Oliveira

Bibliographic record

VenueInterfaces Brasil/Canadá · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsLakehead University
Fundersnot available
KeywordsSociologyHumanitiesArt

Abstract

fetched live from OpenAlex

Discutimos nesse artigo nossas experiências pessoais ao desenvolver umprojeto de pesquisa participativa baseada na comunidade (CBPR) com a PrimeiraNação do Lac Seul para registrar algumas de suas histórias de uso da terra e paratreinar jovens da Primeira Nação e estudantes de nossa universidade em Arqueologia,Antropologia Cultural e Geografia. Com base na literatura acadêmica dos campos deGeografia e Antropologia, ilustramos como ambas as disciplinas influenciaram nossotrabalho e o entendimento de nossas jornadas profissionais e pessoais. Descobrimosprincipalmente que as fases tradicionais de pesquisa acadêmica do projeto e coleta dedados não descreviam adequadamente a fase inicial do projeto e a subsequente troca deinformações. Em vez disso, descobrimos as seguintes fases de pesquisa que se tornaramimportantes: Construção de relacionamentos, Projeto, Aprendizado, Imersão / Coleta dedados e Ativismo / Mudança de perspectivas.

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)0.007
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.993
Threshold uncertainty score0.634

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.009
Science and technology studies0.0400.017
Scholarly communication0.0080.002
Open science0.0030.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.590
GPT teacher head0.596
Teacher spread0.006 · 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.

Study designQualitative
DomainMethods
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".

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Citations1
Published2018
Admission routes2
Has abstractyes

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