Definitions of Esports: A Systematic Review and Thematic Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The esports market has been growing exponentially has been growing exponentially with much interest from industry and academia. Perhaps because of this growth, there is a lack of agreement on what esports actually encompasses. We conducted a systematic review of 461 peer reviewed, full papers that provide a definition of esports. Findings highlighted the growth of the esports field across different domains, and increasing global interest in esports, but a lack of consensus regarding definition of the term. Through thematic analysis we identified nine dimensions across esports definitions. We critically assess these dimensions in terms of their representativeness and utility in describing the multifaceted nature of esports. Our work may help create a shared understanding of what esports is- and is not-capturing a diversity of experiences within organized competitive gaming and supporting continued research growth in this increasingly important domain.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it