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Record W1975229725 · doi:10.1558/genl.2007.1.1.93

What D/discourse analysis can tell us about neoliberal constructions of (gendered) personhood

2007· article· en· W1975229725 on OpenAlexaff
Catherine Kingfisher

Bibliographic record

VenueGender and Language · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsAotearoaPersonhoodSociologyNeoliberalism (international relations)TemporalityGovernmentalityGender studiesDiscourse analysisEpistemologySocial sciencePolitical sciencePoliticsLinguisticsLawPhilosophy

Abstract

fetched live from OpenAlex

How do the commonsense claims of Discourse (systems of knowledge production) relate to those of discourses (informal conversations, texts)? Under what conditions does a Discourse become commonsense and how, when, and under what conditions does it lose this status? How can we track changes in gendered D/discourses over time? This paper explores these questions with reference to the neoliberal, gendered constructions of personhood accompanying welfare reforms in Aotearoa/New Zealand in 1991 and 1996, and the changes that have occurred since Aotearoa/New Zealand began, in 1999, to retreat from neoliberalism. An understanding of the place of neoliberal conceptualizations of personhood in the discourse of poor single mothers and welfare providers, and in policy texts five years after the government shift, calls for a D/discourse analysis that is oriented simultaneously to the problematics of commonsense and temporality.

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)0.012
metaresearch head score (Gemma)0.016
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0090.052
Scholarly communication0.0190.042
Open science0.0020.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.352
Teacher spread0.330 · 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

Citations13
Published2007
Admission routes1
Has abstractyes

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