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Record W1607774287

Making it Better: Colonialism and the Economic Development of First Nations in Canada

2006· article· en· W1607774287 on OpenAlexaffabout
Kelsey Radcliffe Wrightson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsColonialismThird worldReservationGovernment (linguistics)Perspective (graphical)Position (finance)Political economyPolitical scienceSociologyEconomic growthDevelopment economicsEconomicsLaw
DOInot available

Abstract

fetched live from OpenAlex

Economic development is much more than individuals trying to maximize incomes and prestige, as many economist and sociologist are inclined to describe it.It is also about maintaining and developing culture and identity.1 Though much of the discourse surrounding development is orientated primarily to the third world, recent events at the Kashechewan reservation highlight that development issues are not solely a third world problem.Canada is in a very unique position in terms of development in that there is a duality of development.One part of Canadian society is considered part of the first world, while simultaneously, reserves within Canada are often without running water or electricity, and exemplify conditions closer to that of the third world.This paradox of development in Canada allows for a unique perspective on the interactions between a government still reliant on colonial foundations and First People.Namely, conceptualizing development in a dichotomy between developed and underdeveloped creates an underlying colonial discourse, defining progress and development in a particular manner.Thus, much of the discourse surrounding First Nations people has 131 Kelsey R. Wrightson is in her third year of university in the political science department at the University of Victoria.After a brief stint in Visual Arts she discovered a flourishing love/hate relationship with postmodernism and has not looked back since.Her next big adventure is in the direction of Africa, where she is working to build a school in Ghana, and is especially excited to see baby rhinos in Kenya and large hippos in Uganda.She would like to take this opportunity to thank her wonderful support network.It may have taken some encouragement and reassurance but she made it.Thanks everyone!

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.954

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0310.016
Scholarly communication0.0100.002
Open science0.0010.004
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.216
Teacher spread0.204 · 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 designTheoretical or conceptual
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
Published2006
Admission routes2
Has abstractyes

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