Consuming Code: Use-Value, Exchange-Value, and the Role of Virtual Goods in Second Life
Bibliographic record
Abstract
In recent years, there has been significant growth in consumption of commodities in virtual social worlds, such as Second Life, and in the economies that arise from this practice. While these economic systems have been acknowledged and studied, there remains relatively little understanding of the reasons why individuals choose to purchase such goods, despite the fact that reasons for consumption are strong enough to drive a virtual goods industry with annual profits in the millions of dollars. Virtual goods, the author argues, meet no immediate needs for avatars or individuals and, as such, are purchased based exclusively on their exchange- and symbolic-values. Due to the graphical nature of Second Life and the consequent visibility of commodities within the environment, these reasons for purchasing virtual goods are explored in terms of their roles for users, and especially in terms of their potential for expressing wealth, power, status, individuality, and belonging. As such, this paper considers the roles of consumption in a way that relies on and further illuminates theories of consumption and value with respect to virtual environments and commodities.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".