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Record W2586251071 · doi:10.1057/978-1-137-56153-4_13

Too-Late Liberalism: From Promised Prosperity to Permanent Austerity

2017· book-chapter· en· W2586251071 on OpenAlexaff
Laurence McFalls, Mariella Pandolfi

Bibliographic record

VenuePalgrave Macmillan US eBooks · 2017
Typebook-chapter
Languageen
FieldSocial Sciences
TopicFoucault, Power, and Ethics
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsLiberalismGovernmentalityAusterityVerisimilitudeProsperityPolitical sciencePoliticsPolitical economyPower (physics)SubjectivitySociologyLaw and economicsLawEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

In this chapter, we introduce the concept of too-late liberalism to describe both the illiberal potential inherent to liberalism and the most recent form of liberalism, understood not merely as a technique of government but as a truth regime and discursive formation providing the conditions of possibility for a total form of human life. Building on Foucault’s genealogy of liberal governmentality, we explore the relations between truth, power and subjectivity under liberalism to show how its promise of freedom and prosperity gives way, always potentially and now actually, to a reality of insecurity and austerity and how its truth regime of probabilistic veridiction succumbs to plausibilistic verisimilitude as its “political culture of danger” turns into one of fear. We argue that Foucault’s genealogy of neoliberalism in the late 1970s implicitly anticipated liberalism’s too-late quality as the changes in liberal government, notably in its humanitarian and securitarian impulses, since then have demonstrated.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.542
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.047
GPT teacher head0.310
Teacher spread0.263 · 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.

Study designTheoretical or conceptual
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

Citations6
Published2017
Admission routes1
Has abstractyes

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