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Record W3115179505 · doi:10.1108/etpc-06-2020-0055

Reenvisioning space, mobilities and public engagement with young adult literature

2020· article· en· W3115179505 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnglish Teaching Practice & Critique · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMobilitiesOriginalitySociologySpace (punctuation)Value (mathematics)Human geographyEveryday lifeAestheticsEpistemologySocial scienceComputer scienceQualitative researchArt

Abstract

fetched live from OpenAlex

Purpose In an era when engagement in public spaces and places is increasingly regulated and constrained, we argue for the use of literary analytic tools to enable younger generations to critically examine and reenvision everyday spatialities (Rogers, 2016; Rogers et al. , 2015). The purpose of this paper is to consider how spatial analyses of contemporary young adult literature enrich interrogations of the spaces and places youth must navigate, and the consequences of participation for different bodies across those spheres. Design/methodology/approach In a graduate seminar of teachers and writers, we examined literary texts through a combined framework of feminist cultural geography, mobilities and critical mobilities studies. In this paper, we interweave our own spatial analyses of two selected works of young adult fiction with the reflections of our graduate student participants to explore our spatial framework and its potential to enhance critical approaches to literature instruction. Findings We argue that spatial literary analysis may equip teachers and students with tools to critically examine the spaces and places of everyday life and creatively reenvision what it means to be an engaged citizen in uncertain and troubling times. Originality/value While we have engaged in this work for several years, we found that in light of the global pandemic, coupled with the recent antiracist demonstrations, a spatial approach to literary study emerges as a potentially even more relevant and powerful component of literature instruction.

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.

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)0.001
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0030.005
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.256
Teacher spread0.241 · 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