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Record W2025965885 · doi:10.4245/sponge.v3i1.6569

Exploring Epistemic Boundaries Between Scientific and Popular Cultures

2010· article· en· W2025965885 on OpenAlexvenueno aff
Marina Levina

Bibliographic record

VenueSpontaneous Generations A Journal for the History and Philosophy of Science · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsnot available
Fundersnot available
KeywordsMisrepresentationEpistemologyPopular cultureNegotiationSociologySocial sciencePolitical sciencePhilosophyMedia studiesLaw

Abstract

fetched live from OpenAlex

Science studies have long been concerned with the complex interrelationship between scienti?c research and popular culture’s interpretations and reconstructions of scienti?c ?ndings (Kember 2003; Lancaster 2003; Penley 1997, among others). Disparities between the two are often presented as popular culture’s misinterpretation or misrepresentation of scienti?c facts; however, in this essay I argue that a more theoretically lucrative approach understands these con?icts as complex social and cultural negotiations over epistemological boundaries between scienti?c and popular cultures. Understanding such differences is tremendously important in mediated societies where scienti?c research is mostly understood through its representation in the popular culture. In this paper, I examine what is at stake in popular representations of scienti?c research and how the popular culture is often seen as threatening to the epistemic boundaries of scienti?c culture. Using the recent controversy over The Oprah Winfrey Show’ s presentation of controversial medical practices as a case study, this essay examines how distinctions between scienti?c and popular ways of knowing are constructed, represented and managed. I argue that scienti?c knowledge should be viewed as a complex and often con?icted cultural discursive practice that signi?es boundary negotiations between scienti?c and popular cultures.

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 categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.995

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 studies0.0110.008
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.471
GPT teacher head0.393
Teacher spread0.078 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations2
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueSpontaneous Generations A Journal for the History and Philosophy of ScienceSame topicClimate Change Communication and PerceptionFrench-language works237,207