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Record W2969854849 · doi:10.24908/iqurcp.9348

Invisible Languages in Eden Robinson’s Monkey Beach

2018· article· en· W2969854849 on OpenAlexvenueno aff
Sofie Bedard

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeTransliterationSpellingInsiderLinguisticsSpellPoint (geometry)First languageHistoryLiteratureArtSociologyPhilosophyEpistemologyAnthropology

Abstract

fetched live from OpenAlex

Language in Monkey Beach is vital in delineating roles of “insider” and “outsider” within the text. Lisamarie Hill’s inability to speak the Haisla language as fluently as her grandmother, Ma-ma-oo, always endorsed, isolates her from being able to fully understand her Haisla roots. As Ma-ma-oo says: “… to really understand the old stories, you had to speak Haisla" (211). Yet, it is also through the matrilineal line that Lisa inherits the role that secures her a position as a Haisla “insider”. Lisa inherits her grandmother’s and mother’s gift of foresight, and an ability to speak to spirits and the dead. She inherits the language of the old stories, those that by Ma-ma-oo’s logic are unutterable in English. The language of the dead is an invisible language because it is inviolate by colonial forces and it functions outside of Western epistemology, but also because the text itself is written in English. Thus the mainstream reader becomes the “outsider”, denied access to the language of the spirit world, receiving instead an inadequate English translation. The narrative emphasizes the impotence of English translation earlier in the text, noting that: “Haisla has many sounds that don’t exist in English, so it is not possible to spell the words using English conventions” (193). Translational failure becomes manifest in the spelling of Haisla words using transliteration, which become physically fragmented by apostrophes and point to the problems of translation, and to ultimately undermine the task of translating Haisla culture into the “Western” medium of the novel.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.636
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.092
GPT teacher head0.367
Teacher spread0.274 · 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 teacher head, not a consensus.

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
Published2018
Admission routes1
Has abstractyes

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