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Record W2601918730

Collaborative Research with First Nations in Northern Ontario: The Process and Methodology

2016· article· en· W2601918730 on OpenAlexvenueaboutno aff
Denise M. Golden, Carol Audet, Mike Smith, Raynald Harvey Lemelin

Bibliographic record

VenueCanadian journal of native studies · 2016
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsTraditional knowledgeIndigenousClimate changeContext (archaeology)Sociology of scientific knowledgeGeographyPoliticsEnvironmental resource managementEnvironmental ethicsPolitical scienceSociologyEcologySocial scienceArchaeologyLaw
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTIONThe importance of engaging with Indigenous peoples1 in climate change research is evident. Studies have brought attention to the valuable knowledge of Indigenous peoples in climate change adaptation and mitigation (Cruikshank 2001, Macchi et al. 2008), the adaptive capacities of Indigenous peoples to climate change (Devkota, Bajracharya, Narayan, Cockfield & Upadhyay, 2011, Galloway, McLean, Ramo-Castillo & Rubis, 2011) and in the 'co-production of knowledge' on climate change (Berkes 2009). Other studies have discovered drawing on Indigenous knowledge produces a better understanding than western knowledge and scientific methods alone, despite the challenges with integrating the two knowledge systems (Cochran et al. 2008; Bohensky & Mam 2011). Increasing there is the recognition that local and Indigenous knowledge fills gaps in scientific knowledge in remote or hard to access environments, particularly in areas of high environmental priority (Brook & McLachlan 2008). Incorporating the depth and breadth of Traditional Ecological Knowledge (TEK)2 provides invaluable insight on the historic and current status of the land (i.e., biophysical, flora and fauna) and across large geographic areas. Argued by Dowsley (2009) this insight not only expands scientific knowledge, but is necessary in forming appropriate policies in rapidly changing environments. The growing literature from Indigenous scholars also places local experiences in a broader context and is therefore relevant as a knowledge paradigm parallel with western knowledge (Henry at al. 2013) to address climate change.In recent years, Nishnawbe Aski Nation (NAN), a political territorial organization (PTO) representing 49 First Nations in Ontario, Canada, recognised the importance of addressing climate change and its impacts on their communities. First Nations in NAN are Cree, Ojibwe, and Oji-Cree people and parties to the historic Treaty No. 9 and No. 5 (Ontario portion); their territorial homeland covers 2/3 of the province of Ontario spanning -544 000 km2 (NAN 2014). NAN First Nations are predominantly forest-dwelling Aboriginal peoples and the rapid and unpredictable changes on the landscape related to climate change are influencing their traditional activities, food and energy security (Lemelin et al. 2010a; 2010b; 2010c; Golden, Audet, & Smith, 2015). This paper presents the process and methodology of our research collaboration and reviews the fieldwork experience with First Nations in northern Ontario to examine climate change on territorial land. The research collaboration applied Participatory Action Research (PAR) and was supported by the methodological philosophy CREE: C-capacity building, R-respect, E-equity, and E-empowerment (Lemelin & Lickers 2004). The research experience and lessons learned from the collaboration are woven together in the discussions; some research findings are also included in the discussion. The aims of this paper are to evaluate how the research method worked, or did not work, in practice and present best practices for collaborative research with First Nations affected by climate change.During a study the researcher and the research participants are interrelated (Creswell 2007) and interactively exchange data during the research process (Charmaz, 2006; Bernard & Ryan 2010). The recognition that researchers and participants are interrelated and interactive contributors in research presents the opportunity and basis for research collaborations. Research collaborations provide the space and avenue to exchange, on the one hand, a better understanding in the premise and requirements in academic research, and on the other, guidance in research inquiry that is sensitive and beneficial to everyone involved. Past research with Indigenous peoples (and other vulnerable or marginalized groups in society) has not always been respectful, indifferent, and at times, unethical (Cochran et al., 2008). …

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)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.882
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.255
GPT teacher head0.498
Teacher spread0.244 · 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 teacher head, not a consensus.

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

Citations2
Published2016
Admission routes2
Has abstractyes

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