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Narcissism and Neo-Liberalism : Work, Leisure, and Alienation in an Era of Consumption

2007· article· en· W1965977443 on OpenAlexvenueno aff
Matthew McDonald, Stephen Wearing, Jess Ponting

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2007
Typearticle
Languageen
FieldPsychology
TopicNostalgia and Consumer Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsNarcissismPleasureSocial psychologyIdentity (music)PsychologyConsumerismEmptinessSociologyLiberalismAlienationConsumption (sociology)AestheticsPolitical scienceSocial sciencePsychotherapistLawEpistemology

Abstract

fetched live from OpenAlex

The purpose of this paper is to trace some of the links between neo-liberalism, narcissism and the influence of work, leisure and consumer culture on self-identity. By examining narcissism as an instrument of personality and social psychological analysis, we investigate the ways in which self-identity in neo-liberal societies is constructed and fulfilled through interactions with the marketplace, promoting self-interest and success in the form of wealth, admiration and bodily perfection. It is our contention that this process creates narcissistic identities, which attempt to defend the self against the degradation of work in neo-liberal societies, and where anxiety, emptiness and isolation are converted into pleasure and healing through leisure consumerism. In the final analysis we explore some of the links between narcissistic work and leisure, and psychological distress and disorders.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.013
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
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 head0.038
GPT teacher head0.363
Teacher spread0.325 · 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 designTheoretical or conceptual
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

Citations36
Published2007
Admission routes1
Has abstractyes

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