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Record W6925571571 · doi:10.20381/ruor-31107

Land-Based Education for Northern Youth: Exploring the Impacts of On-the-Land Camps in the Northwest Territories

2025· dissertation· en· W6925571571 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Ottawa - Library · 2025
Typedissertation
Languageen
FieldEngineering
Topic3D Modeling in Geospatial Applications
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousTraditional knowledgeStewardship (theology)PhotovoiceArcticCircumpolar starAgency (philosophy)Indigenous educationParticipatory action research

Abstract

fetched live from OpenAlex

Ongoing extractive research and educational systems continue to perpetuate colonial narratives of northern Indigenous communities and the Land which ignore the rights, perspectives, and values of Indigenous Peoples in arctic and subarctic regions around the world, such as the Northwest Territories (NWT). Additionally, Indigenous Peoples face rapid environmental and sociocultural changes that disrupt access to traditional places and practices and limit cross-generational knowledge transfer and decreases opportunities for youth to connect with the Land. Land-based programs aim to provide Indigenous and non-Indigenous youth with spaces to learn about and connect with the Land. However, limited research exists on the experiences of youth in land-based programs, particularly regarding their potential to foster leadership and Land Stewardship among northern youth. Additionally, there is a lack of research documenting the impacts of on-the-land camps as spaces for land-based research projects. Grounded in an Indigenous Research Paradigm (IRP) methodology and Land Stewardship theoretical framework, this land-based research addresses the forementioned gaps in three manuscripts: (M1) "It's not being 'on-the-land'; it's like we are a part of the Land.": Indigenous Youth share visual stories at "on-the-land" camps in the Dehcho; (M2) "A connection with the Land will help youth protect it": Empowering northern youth as Land Stewards through land-based programs in the Northwest Territories and (M3) "Just being on-the-land, the traditional way, eating the food off it. I couldn't ask for a better community to do that in": On-the-land camps as a space for collaborative, reciprocal land-based research. An adapted photovoice method was used to support northern youth to share visual stories of their experiences at four on-the-land camps in the NWT. This research documents the ways the youth were (re)connecting with the Land (M1) and empowered as leaders through Land Stewardship values and practices (M2) at on-the-land camps. By analysing stories from Ka'a'gee Tu, also spelled as K'ágee Tue First Nation (KTFN), youth, Tarek Leahy-Chicot, I provide a reflective examination of this collaborative land-based research to explore holistic meanings and stories of the Land (M3). The results show that land-based programs, like on-the-land camps, are transformative and healing spaces for building relationships between youth and the Land and empowering them as leaders and Land Stewards. Additionally, on-the-land camps are effective spaces for conducting collaborative, reciprocal land-based research. Throughout the dissertation, I include my own personal photographs and poetry as section breaks to create space for the reader to stop, pause, and breathe, and allow for moments of reflection about the ideas shared. This research was conducted and written with love, care, respect, and reciprocity, embedded with my emotions and self-reflection, and it is an act of nurturing and honouring all my relationships.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0110.006
Scholarly communication0.0050.003
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.199
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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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