Reenvisioning space, mobilities and public engagement with young adult literature
Bibliographic record
Abstract
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; Rogerset 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.026 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".