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Record W4240906545 · doi:10.31124/advance.12739499

Dialectics of Time and Space in American Indian Women’s Writings

2020· preprint· en· W4240906545 on OpenAlexaboutno aff
Qasim Shafiq, Ghulam Murtaza, Asma Haseeb Qazi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsCeremonyDialecticHistorySpace (punctuation)Gender studiesArtSociologyAnthropologyArt historyTheologyPhilosophy

Abstract

fetched live from OpenAlex

This study new-historically explores the dialectics of time and space in American Indian women’s writings to explain American Indians’ awareness of and attachment to their surrounding nature and its expression in the contemporary American Indian tribal life. With delimited focus on Louise Erdrich’s Tracks (1988) and Leslie Marmon Silko’s Ceremony (1977), this article analyzes American Indian approach to time and space reflecting Natives’ awareness of their surrounding place. Mythical stories of oral tradition inscribed in Tracks and Ceremony recreate American Indian timeless and macrocosmic realities. American Indian women writers have been selected owing to the matriarchal nature of American Indian social order wherein women have been the conscious carriers of their timeless oral tradition. The two selected novels of different settings express the cultural range of American Indian tribal belt from Canadian border (Tracks’ setting) to Mexican border (Ceremony’s setting). This range is evidence of the synchronic and diachronic integrations and distinctions of American Indian past, present and future.

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)0.005
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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0130.030
Scholarly communication0.0110.005
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.295
Teacher spread0.283 · 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
Published2020
Admission routes1
Has abstractyes

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