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Record W2925918219 · doi:10.22215/etd/2018-13211

Less is More Work: A Governmentality Analysis of Authenticity Within Minimalism Discourse

2018· dissertation· en· W2925918219 on OpenAlexaff
Erin Murphy

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsCarleton University
Fundersnot available
KeywordsMinimalism (technical communication)GovernmentalityConsumerismRhetoricSociologyCritical discourse analysisAestheticsDiscourse analysisAusterityMedia studiesEpistemologyPolitical scienceArtLinguisticsPhilosophyIdeologyLawPolitics

Abstract

fetched live from OpenAlex

At its core, this is a project about the contemporary crisis of authenticity. Using minimalism discourse as a site to explore this crisis, my research into the minimalist lifestyle and its critique of consumerism is guided by two questions. First, how is the concept of authenticity mobilized within minimalism discourse? And second, how does the notion of authenticity contribute to governing the minimalist lifestyle and shaping the minimalist subject? To explore these questions a selection of self-help texts, or pedagogical lifestyle resources, are used. The discursive sites explored herein include guru books, Reddit forums, a documentary, Instagram posts, TED talks, and media coverage on the minimalist lifestyle. These diverse data sites are analyzed using mixedmethods including discourse analysis, frame analysis, and elements of grounded theory, and are shaped by a governmentality approach to theory and methodology. emphasis on consuming to meet basic needs rather than satisfying wants. These are deemed to be more natural, and therefore authentic, ways to consume.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.381
Teacher spread0.336 · 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 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

Citations5
Published2018
Admission routes1
Has abstractyes

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