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Record W3153094520

Living Well Together: Understanding Treaties as Arguments to Share (L'esprit des Traités : le Traité comme Accord de partage)

2018· article· fr· W3153094520 on OpenAlexaboutno aff
Aimée Craft

Bibliographic record

VenueSSRN Electronic Journal · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticultural Socio-Legal Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTreatyIndigenousPossession (linguistics)EthnologyPolitical scienceHumanitiesLand rightsOrder (exchange)NegotiationGeographyLawSociologyPhilosophyBusiness
DOInot available

Abstract

fetched live from OpenAlex

English Abstract: Anishinaabe law tells us that land is not to be owned. Rather, we are in a relationship of respect with the land, with a sense of belonging to the land or “being of the land.” Non-Indigenous legal systems, however, are primarily based in ideas of land ownership and possession. Treaties were made by Indigenous nations and representatives of the Crown in order to settle land questions. For example, the Anishinaabe of Treaty 1 petitioned the Lieutenant-Governor of Manitoba to enter into a Treaty negotiation in order to ensure protection against the encroachment of white settlers who were taking timber from Anishinaabe lands. French Abstract: La loi anishinaabe nous dit que la terre ne peut etre possedee. Nous entretenons plutot une relation de respect avec la terre, au sens ou nous appartenons a cette terre et ou nous en faisons partie. Les systemes juridiques non-autochtones, pour leur part, reposent sur les notions de propriete et de possession du territoire. Des Traites ont ete conclus entre les Nations autochtones et les representants de la Couronne afin de regler des questions de nature territoriale. Par exemple, les Anishinaabe du Traite no 1 ont demande au lieutenant- gouverneur du Manitoba d’entamer des negociations afin de les proteger contre les intrusions des colons blancs qui pillaient le bois sur leurs territoires.

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)0.007
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0140.033
Scholarly communication0.0190.028
Open science0.0020.008
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0110.001

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 head0.083
GPT teacher head0.336
Teacher spread0.253 · 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
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
Published2018
Admission routes1
Has abstractyes

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Same venueSSRN Electronic JournalSame topicMulticultural Socio-Legal StudiesFrench-language works237,207