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Record W4389208644 · doi:10.54337/ojs.bess.v5i1.8138

Polycentric self-governance and Indigenous knowledge

2023· article· en· W4389208644 on OpenAlexaff
Shann Turnbull, Natalie Stoianoff, Anne Poelina

Bibliographic record

VenueJournal of Behavioural Economics and Social Systems · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsIndigenousCorporate governanceSustainabilitySelf-governanceTraditional knowledgeHumanityEnvironmental ethicsPolitical scienceSociologyEcologyManagementEconomicsBiologyLaw

Abstract

fetched live from OpenAlex

This article's main aim is to discuss research exploring how the self-governing practices found in Indigenous societies, biota and modern organisations can be embedded into the constitutions of legal entities to protect and share the wellbeing of humanity, biota and the planet. In this paper, we explore how Australian Indigenous knowledge and practices can be embedded into organisational entities and discuss how this can be achieved by reformatting Ostrom's design principles to be incorporated into corporate constitutions following an ecological form of governance practised by Indigenous Australians. This form of polycentric self-governance can aggregate the voices of minorities representing local environments up to a global level. We use case studies, system science and biomimicry to explore polycentric self-governance and how organisations can adopt it to focus on the wellbeing of all stakeholders. In particular, the paper highlights how Indigenous knowledge can contribute globally to achieving societal sustainability.

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)0.000
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 score0.181
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.145
GPT teacher head0.353
Teacher spread0.208 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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