MétaCan
Menu
Back to cohort
Record W4392350035 · doi:10.18584/iipj.2023.14.3.14789

Navigating across anthropological and Haudenosaunee knowledge: co-developing research using CBPR and Kaswenta (Two-Row Wampum) principles in partnership with Six Nations of the Grand River.

2024· article· en· W4392350035 on OpenAlexaffvenue
Afroza Sultana, Dawn Martin‐Hill, Julie M. Wilson

Bibliographic record

VenueInternational Indigenous Policy Journal · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGeneral partnershipIndigenousTraditional knowledgeSociologyPolitical scienceBiologyEcologyLaw

Abstract

fetched live from OpenAlex

As part of the Ohneganos research project, funded through the Global Water Futures (GWF), we document the ways we worked across Haudenosaunee and anthropological knowledge to assess the impact of water insecurity on holistic maternal health. This research was led by the Six Nation Birthing Center (SNBC), inspired by Haudenosaunee Kaswenta treaty principles. We utilized community-based participatory research (CBPR) and Indigenous research methods (IRMs), such as storytelling, to find common ground of dialogue and reciprocity. In doing so, this research goes beyond traditional anthropological ways of data collection and fieldwork and highlights the importance of active community direction and participation. We argue that different knowledge from the researchers does not need to be ignored or reduced to one singular perspective to work across worldviews. Instead, acknowledging and highlighting the differences will lead to innovative methods and scholarship. This paper contributes to the literature of research methods and policies and will be helpful to Indigenous communities and non-Indigenous researchers working together.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.917

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.132
GPT teacher head0.462
Teacher spread0.330 · 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.

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

Citations3
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueInternational Indigenous Policy JournalSame topicAgriculture and Rural Development ResearchFrench-language works237,207