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Reflexões sobre a postura do pesquisador em pesquisas em contextos interculturais: desafios e estratégias para a co-construção de conhecimentos

2025· article· pt· W4417120743 on OpenAlexaff
Mariá Boeira Lodetti, Vitoria Nathália Do Nascimento, Lucienne Martins Borges

Bibliographic record

VenueREMHU Revista Interdisciplinar da Mobilidade Humana · 2025
Typearticle
Languagept
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsField (mathematics)Perspective (graphical)Meaning (existential)Order (exchange)Face (sociological concept)Subject (documents)

Abstract

fetched live from OpenAlex

Resumo: Este artigo analisa a postura do pesquisador em pesquisas qualitativas realizadas em contextos interculturais. As reflexões são oriundas de experiências das autoras com estudos desenvolvidos no Brasil e no Canadá. Inicialmente, apresenta-se uma revisão da literatura sobre os principais desafios metodológicos enfrentados em pesquisas em contextos interculturais. Em seguida, explora-se a Etnopsiquiatria como referencial ético, teórico e metodológico, especialmente os conceitos de complementaridade e contratransferência. Por fim, partindo de desafios vividos pelas autoras, propõe-se estratégias de adaptação de pesquisas qualitativas em contextos interculturais. A análise enfatiza a importância da escuta sensível, da co-construção de conhecimentos e do enfrentamento das assimetrias de poder. Além disso, adaptações linguísticas, uso de diário de campo e utilização do percurso comentado são discutidos. O artigo contribui para a ampliação do debate sobre práticas metodológicas sensíveis e comprometidas com a complexidade da construção de conhecimento em contextos interculturais no campo das ciências humanas e sociais.

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)0.017
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.002
Science and technology studies0.0050.004
Scholarly communication0.0050.001
Open science0.0030.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.161
GPT teacher head0.521
Teacher spread0.360 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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