Bibliographic record
Abstract
ABSTRACT Although prior literature has emphasized marketplace participants' co‐construction mostly in terms of symbolic, oral, or emotional aspects of a consumption experience, there has not been much attention paid to potential concerns around success, failure, strategies, risk, dependence, and competition involved. This article, by building on the existing body of research, introduces the notion of performancescapes to better understand these issues as they relate to participant performances in the co‐construction of marketplace experiences. Performances have the character of being an accomplishment involving an interactive quality and an element of risk. Accordingly, highlighting competencies and effectiveness rather than just the meaning enables us to concentrate on issues of success, failure, and risk. Furthermore, it is not uncommon to examine the marketer side of marketplace performances, but the customer side is generally neglected or assumed to be more passive. In this paper, we explore some of the ways through which service providers and clients participate in a marketplace stage as a performancescape in order to have a successful co‐constructed performance. We further maintain that the performative competencies of consumers can be as significant as that of marketers or service providers. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".