MétaCan
Menu
Back to cohort
Record W7010499202

Indigenous People in the Global Context

2018· article· en· W7010499202 on OpenAlexaboutno aff

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousContext (archaeology)Natural (archaeology)Traditional knowledgeNatural heritage
DOInot available

Abstract

fetched live from OpenAlex

There are 350 million indigenous people in the world, all are in a similar circumstance. They are still classically colonized, robbed of their territory and live on the periphery of a globalized imperial economy that is threatening the globe. Generally speaking the Indigenous people have been “dumbed down” to a pre-civilized state. It is generally agreed that Indigenous people were non-scientific, non-theoretical, incapable of abstraction and so forth. In fact, science is just now catching up to some key understandings that Indigenous people have had for a very long time. For the most part, Indigenous people are oral and therefore cannot be believed, nor studied by western intellectuals. Why is this a problem? About the Lecturer: Ms. Maracle is the author of a number of critically acclaimed literary works including: Ravensong [novel], Canadian Scholar’s Press, Bobbi Lee [autobiographical novel], Three O’clock Press, Daughters Are Forever, [novel] Theytus Will’s Garden [young adult novel] Theytus books, “Bent Box” [poetry] Theytus books, “I Am Woman” [non-fiction], Polestar/Raincoast and the co-editor of a number of anthologies including the award winning publication, “My Home As I Remember” [anthology] Natural Heritage books. Ms. Maracle is widely published in anthologies and scholarly journals worldwide. Ms. Maracle is a member of the Sto: Loh nation.

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)0.001
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.085
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.010
Scholarly communication0.0050.005
Open science0.0010.007
Research integrity0.0030.004
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 head0.019
GPT teacher head0.277
Teacher spread0.258 · 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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueWestern CEDAR (Western Washington University)Same topicIndigenous Health, Education, and RightsFrench-language works237,207