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Record W7005761951

Research Guidelines with Indigenous Peoples

2020· article· en· W7005761951 on OpenAlexaboutno aff

Bibliographic record

VenueSOURCE Sheridan's Institutional Repository (Sheridan College) · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDermatological and Skeletal Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousIdentity (music)ColonialismGenocideTraditional knowledgeFocus groupInterpretation (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

“Research is important to reconciliation in the creation of a national memory” (Senator Murray Sinclair, National Dialogue, 2019). This document is designed to provide Sheridan faculty, staff and students with suggested practices to guide their research when working with Indigenous Peoples and to establish a set of standards to ensure that all research activities are undertaken with care and respect. When it comes to research, colonialism and cultural genocide have created a history of mistrust for Indigenous Peoples in relation to the intentions of non-Indigenous Peoples. These factors have led us to develop guidelines, applications and processes in order to ensure that research projects involving Indigenous Peoples will be conducted in a safe, collaborative and positive manner. For For the purposes of these guidelines, the term “Indigenous Peoples” will be used to represent any person who self-identifies as being First Nation, Inuit, or Métis. These guidelines are to be followed when research includes Indigenous Peoples in any way, regardless of the overall focus of the research. Indigenous research is research that includes a major Indigenous component such as: Research conducted on First Nations, Inuit, or Métis lands; Projects where Indigenous identity is a criterion for research participation; Research that seeks input from participants regarding Indigenous culture, heritage, artifacts, traditional knowledge or unique characteristics of Indigenous Peoples; Research in which Indigenous identity or membership in an Indigenous community is used as a variable for the purpose of data analysis; Projects where interpretation of data results refers directly to Indigenous communities, peoples, language, history or culture; and, Research that is likely to affect the welfare of Indigenous Peoples. (TCPS 2; Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada, and Social Sciences and Humanities Research Council of Canada, 2018). \nThese Guidelines have been compiled based on a review of the literature, the Tri-Council policy on ethical research practices with human participants, and existing protocols and best practices for ethical and appropriate research practice when working with Indigenous Peoples from other organizations and post-secondary institutions. While cultural traditions, languages, customs, laws and their meanings are unique and specific to each individual nation, we are basing these guidelines more broadly on the common traditions and values of Ontario First Nations communities. However, it is imperative that researchers ensure they familiarize themselves with the culture, values and traditions of whichever community with whom they are working. Sheridan’s Sheridan’s Centre for Indigenous Learning and Support provides a host of different resources that may be useful for those interested in research with Indigenous Peoples, in combination with these Guidelines (sheridancollege.libguides.com/Indigenous). In addition, there are other resources which can also provide a comprehensive overview of information to support better understanding and education about Indigenous cultures (www.anishinaabemdaa.com/#/).

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)0.275
metaresearch head score (Gemma)0.323
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.725
Threshold uncertainty score0.894

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2750.323
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0060.007
Science and technology studies0.0120.016
Scholarly communication0.0130.014
Open science0.0100.013
Research integrity0.0230.023
Insufficient payload (model declined to judge)0.0240.026

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 head0.032
GPT teacher head0.283
Teacher spread0.252 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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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Citations0
Published2020
Admission routes1
Has abstractyes

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