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Record W7106342288 · doi:10.5281/zenodo.17674732

A View of the Chemical Valley: Waste and Wasting in Jennilee Austria- Bonifacio's "The Outsiders"

2025· article· en· W7106342288 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)WastingGlobalizationPower (physics)Environmental justiceNeoliberalism (international relations)Scale (ratio)Ecological crisis

Abstract

fetched live from OpenAlex

This paper analyses “The Outsiders”, the sixth short story included inCanadian Jennilee Austria-Bonifacio’s 2023 collection Reuniting with Strangers, from theproductive juncture at the intersection of environmental and eco-social justice theories.With special attention to the local-international scale of globalisation processes, and thedefiance brought to light by the attempt at narrating eco-social violence, it is proposedfirst that the so-called Anthropogenic Great Acceleration, which chronologicallyencloses Filipinos’ first massive arrivals at Canada, also provides a context in which toweave a critical dialogue between turbo-capitalist ecological disposability and humandispensability within toxic neoliberal power structures. Secondly, it is argued that,within a general context of dynamic wasting relations, the story articulates a generalrepoliticisation of the current socio-ecological crisis in which a transnational alliancebased on sharing and caring reduces power asymmetries and provokes a collapse of thedualities scaffolding concepts like home and outsider to advocate instead their multiscalarrefiguration.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0320.044
Scholarly communication0.0080.004
Open science0.0010.006
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.024
GPT teacher head0.208
Teacher spread0.185 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicEcocriticism and Environmental LiteratureFrench-language works237,207