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Record W7005649873

Re-Occupying the Archipelago: The Potential of Unified Governance in the Thousand Islands Region through Application of the Haudenosaunee Great Law of Peace

2023· dissertation· en· W7005649873 on OpenAlexaboutno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldChemistry
TopicAdvanced Synthetic Organic Chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousCorporate governanceIndigenizationPoliticsReciprocity (cultural anthropology)NegotiationSustainable developmentWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores the potential Indigenization of governance in the Thousand Islands region through integration of Haudenosaunee political philosophy to better inform methods by which local governing bodies make decisions pertaining to development of the region. By considering forms of governance that are in and of themselves Indigenous to the region, problems pertaining to overdevelopment, racial equity, and conservation may be addressed. The development of a comprehensive framework for the sustainable management and development of Canada’s Thousand Islands region may be used to promote coexistence and reciprocity amongst all stakeholders in the area. Through a historical analysis of the site, regional treaties, and Indigenous philosophy, new methods of interaction that contrast hierarchical systems of governance arise as alternatives. The application of the structure of the traditional grand council of the Haudenosaunee, offers a method by which consensus can be achieved by large groups of individuals, prioritizing ideas that benefit the broader community, the land, and generations to come.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.009
GPT teacher head0.211
Teacher spread0.202 · 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 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
Published2023
Admission routes1
Has abstractyes

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