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Record W4231472954 · doi:10.24908/iqurcp.8952

The Social Construction of Dysfunction and Disorders: What Role Does the Pharmaceutical Industry Play?

2016· article· en· W4231472954 on OpenAlexvenueno aff
Nicole Persall

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2016
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsPharmaceutical industrySexual dysfunctionHuman sexualityErectile dysfunctionOrder (exchange)Sexual functionFunction (biology)Female sexual dysfunctionPsychologyBusinessPublic relationsMarketingMedicinePsychiatryPharmacologyPolitical scienceLawFinance

Abstract

fetched live from OpenAlex

There has been widespread controversy regarding the pharmaceutical industry’s motive to promote and sell new drugs pertaining to sexual health. In this paper I will bring up a number of different authors who feel that the definition of ‘sexual health’ has been purposely redefined in order to create a market for a drug whose need is questionable. This paper investigates and raises questions about the veracity of diseases heavily promoted and marketed by the pharmaceutical industry, such as female sexual dysfunction disorder. Is it truly the female equivalent to male erectile dysfunction? Or is it the avaricious creation of pharmaceutical companies in a sly endeavor to increase sales of products like Viagra? Next, I look at the enormous impact pharmaceutical companies have had on shaping our everyday definitions of what is ‘normal’ in terms of sexual functioning. Also, the effects of standardizing diagnosis are considered, and finally, I investigate the costs of reducing sexual dysfunction to a physiological cause and how pharmaceutical industries strive to create a universalized, function-focused sexuality in which physiology dictates sexual conduct.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.006
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.109
GPT teacher head0.429
Teacher spread0.321 · 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
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

Citations0
Published2016
Admission routes1
Has abstractyes

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