Bibliographic record
Abstract
Purpose The purpose of this paper is to explore what an idiosyncratic and dynamic sense of belonging entails for consumption in a lifestyle sport, an ever shifting and progressing world in which individuals engage in community while also seeking to individuate their own sense of belonging. Design/methodology/approach The authors adopt an ethnographic approach in the context of a regional skateboarding community. Over a year at local skateparks, we interviewed 15 well-established, committed members of the community identified by others (through snowball techniques) to allow us to delve into the phenomenon. These interviews were conducted as part of the primary author's doctoral thesis (See Harris, 2011). Findings An idiosyncratic and dynamic sense of belonging is prevalent in the lifestyle sport community, even among well-established members. This is reflected in and motivated by a variety of consumption, as well as overconsumption practices. Practical implications Understanding the idiosyncratic and dynamic nature of a sense of belonging allows marketers to design offerings to effectively deal with the ambiguities of belonging but also raises the potential for the destructive use of marketing. Originality/value The authors demonstrate how approaching belonging through a dynamic and idiosyncratic sense of belonging provides a deeper understanding of belonging and related consumption activities in a lifestyle sport.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".