A Study of Cultural Dilution and Influencer Advertising in Samit Basu’s ‘Chosen Spirits’
Bibliographic record
Abstract
The rapid growth of cultural consumption has led to a nearly seamless generation of hyperrealities. This generation is accentuated through the swift and inundated barrage of advertisements that have permeated all modes of expression in mainstream media. This article explores cultural dilution in the context of the convergence of art, advertising, and hyperrealities. Drawing on a textual analysis of Samit Basu's novel ‘Chosen Spirits’(2020), Baudrillard’s notions of hyperreality espoused in ‘Simulacra and Simulation’(1994), and a close study of influencer advertising and its effects, this study dissects the intricate relationship between art and commerce and its subsequent implications for cultural significance. The paper argues that blending art and advertising creates a continuous flow of hyperrealities, eventually diluting the represented culture. This process leads to the convergence of the once distinct realms of art, culture, and commerce, wherein culture becomes a consumable object. Advertising leeches, dilutes, and duplicates significant elements from its source, further blurring the boundaries between the two domains. The symbiotic relationship between advertising, culture and consumption is catalysed by technology. Consequently, the gormandised culture's value diminishes, and the communication gap between producers and consumers widens. In addition to transforming the nature of artistic expression, it impacts the authenticity and integrity of cultural production. The complex dynamics that shape contemporary cultural landscapes are unveiled by analysing how advertising and hyperrealities intertwine with art and culture. This subsequently invites critical reflection upon the implications of cultural dilution, the commodification of art, and the role of technology in reshaping cultural identities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".