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Record W4408039175 · doi:10.1017/s0001972024000779

James C. Scott in Kinshasa, and a response to Jeremiah Arowosegbe

2024· article· en· W4408039175 on OpenAlexaff
Pedro Monaville

Bibliographic record

VenueAfrica · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Identity, and Health
Canadian institutionsMcGill University
Fundersnot available
KeywordsArtPhilosophyHumanitiesTheology

Abstract

fetched live from OpenAlex

When the American political scientist James C. Scott passed away in July 2024, tributes praised him as one of the most influential thinkers of his generation. 1 Building on years of ethnographic research in Southeast Asia, his numerous books offered new ways of thinking about subaltern resistance, as well as the mechanisms of state oppression and control. A self-professed anarchist, he organized against the Vietnam War as a junior faculty at the University of Wisconsin in the latter part of the 1960s, and he maintained a forty-six-acre farm for decades while teaching at Yale. While obituaries widely remembered Scott as a figure of integrity, some dissonant voices on social media commented more negatively on his involvement with the CIA as a young man and as a leader in the United States National Student Association (USNSA). The political scientist Karen Puget first brought this episode in Scott’s life to light in a book that carefully exposed the ties of the USNSA with US intelligence (Puget 2015). Puget showed how, in the 1950s and 1960s, what was then the most important student organization in the USA allowed itself to be fully infiltrated by the government. The young liberal-minded students at the helm of the organization worked hand in hand with CIA handlers to curb Soviet influence among their peer organizations in Europe, Asia and Africa. For a few years, after graduating from Williams College and before embarking on his doctoral studies at Yale, Scott occupied a prominent role among these young shadow Cold Warriors, first as the USNSA’s representative in Paris and later as its vice president in charge of international affairs.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.636
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.343
Teacher spread0.309 · 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 teacher head, 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

Citations1
Published2024
Admission routes1
Has abstractyes

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