Extending Diderot unities: How cosmetic surgery changes consumption
Bibliographic record
Abstract
Abstract Consumers engage in transformative practices such as cosmetic surgery to shape a new self that satisfies personal and social expectations. Yet, we lack an understanding of how cosmetic surgery and the consequent changes to a consumer's self affect their consumption practices. Building on Diderot unities we explore how cosmetic surgery influenced consumption practices of 10 female consumers postcosmetic surgery. Prior work on Diderot unities suggests that it is a new object inspiring the consumption of additional objects. Extending the notion of Diderot unities, we posit that also a new self brings changes in the constellation of consumption objects. Specifically, cosmetic surgery, the self, and material consumption practices are tied together by an expanded view of Diderot unities as not only involving people and objects, but also adding experiences. A newly surgically enhanced person perceives an imbalance between the assemblage of their self and self‐expressive objects. This imbalance sets off a series of purchases to restore balance by acquiring possessions and experiences that match their new magnificent self. Purchases extend to areas such as fashion objects, grooming objects and experiences, as well as experiences related to personal well‐being, vacation and leisure.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".