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Record W1954079092 · doi:10.20360/g23s3g

What kind of pen do I need to use to write my culture and my language?

2011· article· en· W1954079092 on OpenAlexaffvenue
Satoru Nakagawa

Bibliographic record

VenueLanguage and Literacy · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Communication, and Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOralityLiteracyNarrativeIndigenousPoetrySociologyIndigenous cultureStorytellingLiteratureLinguisticsHistoryAestheticsPsychologyArtPedagogyPhilosophy

Abstract

fetched live from OpenAlex

Through a form of narrative inquiry involving the use of vignettes and ruminations about present and past, the author examines the role(s) of orality, literacy, and aurality in the intergenerational transmission of his language and culture. Weaving together stories from childhood, memories, and translations of his grandmother’s poetry, the author raises questions about how we, as Indigenous peoples, might ensure that we are able to teach our own next generations our spirits, hearts, being/knowing of the world and who we are as human beings now that oral cultures are being discarded--or worse, written down.

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)0.003
metaresearch head score (Gemma)0.031
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 score0.015
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.008
Scholarly communication0.0110.013
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0150.009

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 head0.027
GPT teacher head0.338
Teacher spread0.311 · 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

Citations3
Published2011
Admission routes2
Has abstractyes

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