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Record W4411836770 · doi:10.54103/milanoup.213.c404

Chapter 1 - South to North Multispecies Co-Migrations in the Wake of Rachel Carson and Donna Haraway

2025· book-chapter· en· W4411836770 on OpenAlexaboutno aff
Carmen Concilio

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersSorbonne UniversitéUniversità degli Studi della BasilicataCentre National de la Recherche ScientifiqueEuropean CommissionYale UniversityUniversity of CambridgeLinköpings UniversitetUniversity of OxfordHarvard UniversityPrinceton University
KeywordsWakeEnvironmental ethicsHistoryPhilosophyEngineering

Abstract

fetched live from OpenAlex

The volume offers a multidisciplinary inquiry into the manifold representations of the South(s), approached through an ecocritical and decolonial lens. Edited by Carmen Concilio and Alberto Baracco, the volume gathers contributions from scholars across literature, philosophy, media and visual studies to interrogate the South(s) not simply as a geographic entity, but as a dynamic cultural and epistemological construct. Divided into two sections—respectively devoted to “Literary, Ecocritical, Decolonial, and Comparative Readings” and “Images, Representations, and Visual Cultures”—the volume explores how Souths are imagined, narrated, and visualized across temporal, spatial, and media boundaries. Essays address oceanic and blue humanities, multispecies entanglements, ecological ethics, postcolonial narratives, environmental activism, and visual ecocriticism. Through its wide-ranging and timely perspectives, the volume offers a nuanced exploration of ecocritical concerns, capturing the shifting, dynamic quality of Souths and their role today in postcolonial literature, audiovisual production, and the humanities.

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)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.008
Scholarly communication0.0070.006
Open science0.0010.005
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0160.002

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 head0.059
GPT teacher head0.358
Teacher spread0.299 · 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
GenreOther

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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