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Record W3107828344 · doi:10.1177/0263775820970945

In the wake of logistics: Situated afterlives of race and labour on the Magdalena River

2020· article· en· W3107828344 on OpenAlexfundno aff
Austin Zeiderman

Bibliographic record

VenueEnvironment and Planning D Society and Space · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsnot available
FundersUniversity of TorontoDurham UniversityUniversity of California, San DiegoLondon School of Economics and Political Science
KeywordsSituatedRace (biology)EthnographySociologyModernityGender studiesAnthropologyPolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

Based on ethnographic fieldwork conducted aboard a cargo boat on Colombia’s Magdalena River, and on historical accounts of fluvial transport, this article examines the racial formations on which logistics depends. Logistics is organized around flows at the heart of capitalist modernity, which are made possible by labour regimes whose racial underpinnings have both persisted and changed over time. Tracking continuities and divergences in riverboat work along the Magdalena River, I propose that our understanding of logistics is enriched by attending to historical articulations of race and labour. Inspired by scholars who reckon with the afterlives of racial slavery as well as by those who track precisely how that legacy unfolds in geographically and historically situated ways, I propose the analytic of situated afterlives, which focuses attention on the persistence of racial hierarchies and on their perpetual instability.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.014
Scholarly communication0.0040.004
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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

Citations27
Published2020
Admission routes1
Has abstractyes

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