The massifying consumption of embodied goods in an advanced capitalist state: Capital, economic anxieties and social networks
Bibliographic record
Abstract
Abstract Embodied goods like cosmetic surgery comprise a unique and growing consumer industry, most of all in the Asia‐Pacific, yet the rationalisation processes motivating their purchase are less understood. Addressing this lacuna, this article builds upon open‐ended surveys and semi‐structured interviews of consumers in Seoul, South Korea to articulate a relational approach to examine the rationalisation of purchases of cosmetic surgery as an embodied good. Theorised through the conceptual lens of Bourdieusian capital, participant accounts point to macro‐level economic anxieties that inform a micro‐level cognitive logic of competition through which consumers rationalise the purchase of embodied goods as a form of aesthetic capital. When performed, this capital is believed to offer actors social distinction that provides workplace and social networking advantages by impressing gatekeepers and alters. Participants are shown to reconceptualise their bodies in a means‐end orientation for upward mobility but stress their resignation and powerlessness in being forced to adopt this instrumental reconceptualisation as a response to intensifying economic hardships in contemporary capitalist South Korea.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".