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Record W1990315103 · doi:10.1177/0270467606295973

Narrative Magic and the Construction of Selfhood in Antidepressant Advertising

2007· article· en· W1990315103 on OpenAlexaff
Jeffrey Stepnisky

Bibliographic record

VenueBulletin of Science Technology & Society · 2007
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsNarrativeMAGIC (telescope)Agency (philosophy)PillPsychoanalytic theoryPsychoanalysisPsychologySociologyAdvertisingSocial psychologyLiteratureArtMedicineSocial science

Abstract

fetched live from OpenAlex

This article examines the way in which selfhood is constructed in direct-to-consumer advertisements for antidepressant medications. The sample consists of advertisements that appeared in nine popular magazines between 1997 and 2005, television commercials that ran between 2003 and 2005, and online promotional Web sites. The analysis is divided into three sections. First, it is argued that the ads rely on metaphors of communication, information exchange, and plenitude to construct a relationship between biology and selfhood. Second, in offering the choice for antidepressant treatment, the ads grant individuals a new capacity for the exercise of personal agency. Third, the author describes antidepressants as pills that perform a narrative “magic.” In contrast to religious and psychoanalytic narratives that required individuals to incorporate disavowed elements of their selves into an ongoing life narrative, antidepressants are medications that allow individuals to put aside, or jump over, inexplicable and painful moments in their life.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.023
Scholarly communication0.0080.011
Open science0.0010.004
Research integrity0.0010.002
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 head0.008
GPT teacher head0.303
Teacher spread0.296 · 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.

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

Citations11
Published2007
Admission routes1
Has abstractyes

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