MétaCan
Menu
Back to cohort
Record W7031577918

[no title]

2022· other· en· W7031577918 on OpenAlexfundaboutno aff

Bibliographic record

VenueDirectory of Open access Books (OAPEN Foundation) · 2022
Typeother
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
FundersAboriginal Affairs and Northern Development CanadaCrown-Indigenous Relations and Northern Affairs CanadaIndigenous Services CanadaIndigenous and Northern Affairs Canada
KeywordsProclamationIndigenousDutyFiduciaryState (computer science)Natural resourceLand lawLand rights
DOInot available

Abstract

fetched live from OpenAlex

Based on extensive fieldwork and oral history, The Terms of Our Surrender is a powerful critical appraisal of unceded indigenous land ownership in eastern Canada. Set against an ethnographic, historical and legal framework, the book traces the myriad ways the Canadian state has successfully evaded the 1763 Royal Proclamation that guaranteed First Nations people a right to their land and way of life. Focusing on the Innu of Quebec and Labrador, whose land has been taken for resource extraction and development, the book strips back the fiduciary duty to its origins, challenging the inroads which have been made on the nature and extent of indigenous land tenure—arguing for preservation of land ownership and positioning First Nations people as natural land defenders amidst a devastating climate crisis. It offers a voice to the Innu people, detailing the spirituality practices, culture and values that make it impossible for them to willingly cede their land. The text is intended to bridge the gap in knowledge between legal practitioners and those working at the intersections of human rights, social work and public policy. The book offers a potent template for how we can use the law to fight back against the indignities suffered by all indigenous peoples.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesOpen science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.977
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0090.014
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9830.006

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 head0.095
GPT teacher head0.385
Teacher spread0.290 · 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; both teacher heads agree on what is shown here.

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 routes2
Has abstractyes

Explore more

Same venueDirectory of Open access Books (OAPEN Foundation)Same topicSpecies Distribution and Climate ChangeFrench-language works237,207