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Record W6980844936

Cultures of Indigenous Diplomacy – A Digital Conference. Presentations Playlist

2022· other· en· W6980844936 on OpenAlexaboutno aff

Bibliographic record

VenueRepository@Hull (Worktribe) (University of Hull) · 2022
Typeother
Languageen
FieldMaterials Science
TopicMaterial Selection and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousDiplomacySovereigntyClanPoliticsAlliancePower (physics)
DOInot available

Abstract

fetched live from OpenAlex

The Conference showcases reflections on themes linked to Dr Pedri-Spade’s work Material Kwe. The aim is to create space for interdisciplinary dialogue on intercultural expressions of diplomacy, through art and making, material culture including wampum, language and narration in Council speech, food, gender, and languages of law and sovereignty.Presentations include:Alex Jacobs-Blum, Lower Cayuga Nation of Six Nations of the Grand River Territory and German, “Finding my way back through visual storytelling”Rick Powless, Six Nations, Red Seal Chef: "yakunhéhkwʌ: Our Sisters", a cooking demonstration of Haudenosaunee traditional foodsSusan Hill, Associate Professor, University of Toronto: “Haudenosaunee Women and Diplomacy”Great Lakes Research Alliance (Heidi Bohaker, Alan Corbiere, Autumn Epple, Bradley Clements): “Great Lakes Diplomacy through Cultural Heritage”Damien Lee, Anishinaabe from Fort William FN, Canada Research Chair in Biskaabiiyang and Indigenous Political Resurgence: “Asunjigun and Anishinaabe Political Theory”Ken Parker, Seneca Nation, Indigenous horticulturalist and landscape professional: "Food Sovereignty and the Power of Indigenous Planting"Naomi Recollet, Anishinaabe-kwe (Odawa/Ojibwe), Crane Clan from the Wiikwemkoong Unceded TerritoryDale Turner, Associate Professor of Political Science, University of TorontoCeleste Pedri-Spade, Associate Professor and Queen’s National Scholar in Indigenous Studies, Queen’s University

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.111
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0060.004
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1110.019

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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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