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Record W7053344680

We'd rather be 'red' than dead: embracing one's diference through selected Native Canadian fiction for children and young adults

2011· dissertation· en· W7053344680 on OpenAlexaboutno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2011
Typedissertation
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsnot available
Fundersnot available
KeywordsResistance (ecology)Identity (music)Variety (cybernetics)George (robot)HavenCultural identityNarrative
DOInot available

Abstract

fetched live from OpenAlex

Native Canadian fiction for children and young adults can be viewed as an important means of cultural transmission and socialisation that contributes, to a great extent, to a community‟s collective identity. Here begins the first problem posed to us: trying to define the concept of culture and to examine in what way(s) oral heritage forms a part of it. Then, some other questions arise because in Canada, the haven of multiple cultures and ethnicities, debates about national identity re-surface repeatedly and continue to haunt the collective imagiNation of the country. Finding out the place of Native peoples and their literatures is even a greater difficulty, due to the legacy of colonialism. Despite the difficulties, new voices are currently being authorised as Canadian, and difference has now turned into the distinctive feature of the national literature. Jeannette Armstrong, an Okanagan writer, artist and educator, is well aware of the strength that stems from this variety of cultures and, in her works, she advocates for a plurality of voices within and outside of her community. Using Armstrong‟s fiction for children and young adults, and looking briefly at some other works by Tomson Highway, George Littlechild, Thomas King and C. J. Taylor, this dissertation examines how literature can be read as a site of resistance and/or of cross-cultural exchange connecting diverse people of different nationalities, generations, languages, religions, genders and social conditions.

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)0.004
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: none
Teacher disagreement score0.146
Threshold uncertainty score0.304

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0260.015
Scholarly communication0.0080.002
Open science0.0020.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.034
GPT teacher head0.305
Teacher spread0.272 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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