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Record W1517587482

“Don’t Call Me Eskimo”: Representation, Mythology and Hip Hop Culture on Baffin Island

2009· article· en· W1517587482 on OpenAlexaffabout
Charity Marsh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsContextualizationEthnographyMythologyPoliticsSociologyRepresentation (politics)Media studiesIdentity (music)Argument (complex analysis)AnthropologyGender studiesHistoryAestheticsArtPolitical scienceLinguistics
DOInot available

Abstract

fetched live from OpenAlex

Abstract: Through a contextualization of the song, “Don’t Call Me Eskimo, ” which was launched on the interactive website YouTube in 2007 and an analysis of three examples of hip hop culture drawn from her ethnographic fieldwork on Baffin Island in June/July 2008, the author makes the argument that hip hop culture in Nunavut enables a re-working of contemporary Inuit identity. As part of this re-working, Inuit youth mediate representations of themselves and their current lived experiences through mobile technologies and local networks, challenging common stereotypes and reified identities that continue to circulate in political, cultural, and national discourses. You Can’t Stop the Hip Hop!2 “You can’t stop the hip hop! ” is a statement of significance and provocation – a declaration that has been professed to me (a hip hop scholar, researcher, fa-cilitator, and enthusiast) by young people living both in the northern regions of Canada on Baffin Island and those living in southwestern Canada in the prairie provinces of Saskatchewan, Manitoba, and Alberta. To understand the complex meaning(s) of this statement, one needs to consider the continually

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.820

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0250.029
Scholarly communication0.0060.002
Open science0.0020.005
Research integrity0.0020.003
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 head0.034
GPT teacher head0.388
Teacher spread0.355 · 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 designQualitative
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

Citations14
Published2009
Admission routes2
Has abstractyes

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