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TRANSLATION AND CROSS-CULTURAL ADAPTATION OF THE KNOWLEDGE TRANSLATION PLANNING TEMPLATE FOR THE BRAZILIAN CONTEXT

2023· article· en· W4389782604 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTexto & Contexto - Enfermagem · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHealth Education and Validation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsContent validityEquivalence (formal languages)Semantic equivalenceIndex (typography)Consistency (knowledge bases)Adaptation (eye)Knowledge translationTest (biology)Context (archaeology)Meaning (existential)PsychologyMedical educationComputer scienceLinguisticsMedicineKnowledge managementArtificial intelligencePsychometricsWorld Wide WebHistoryClinical psychology

Abstract

fetched live from OpenAlex

ABSTRACT Objective: to translate, cross-culturally adapt, and validate the content of the Knowledge Translation Planning Template, a research dissemination planning tool, into Brazilian Portuguese. Method: this is a methodological study, sequentially divided into six stages: initial translation, translation synthesis, back-translation, judges' committee, pre-test, and approval of the adapted version by the instrument author. The judge's committee assessed content validity using the modified Kappa and Content Validity Index. The test was conducted with teachers and students from a Federal University of Santa Catarina graduate program. Results: the process of translating and back-translating the tool showed no discrepancies in terms of meaning. The committee was composed of seven judges who carried out semantic, cultural, and conceptual evaluations and made notes on the translation of the content. At this stage, the content validity showed excellent values for the Content Validity Index and modified Kappa, with 0.99 and 0.816, respectively. The tool was tested with 30 teachers and postgraduate students, where 90% of the respondents considered the tool to be sufficiently comprehensive and that all the items were relevant to the purpose of the instrument. In the last stage, the documents were analyzed together with the author of the original tool and the final version was approved. Conclusion: the Modelo de Planejamento de Tradução do Conhecimento results from a careful translation process, cross-cultural adaptation, and tool content validation. This has resulted in a tool that is applicable and understood by the target audience, which shows consistency in the equivalence of translation and cross-cultural adaptation for Brazil.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.794
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.784
GPT teacher head0.600
Teacher spread0.183 · 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