“Like Ships in the Night” and the Paradox of Distinctiveness for Sport Management: A Citation Network Analysis of Institutional Theory in Sport
Bibliographic record
Abstract
A central issue within sport management is the extent to which the field should develop a distinctive theoretical knowledge base. This paper empirically investigates the connectedness within (intrafield) and between (interfield) management and sport management disciplines in one specific knowledge domain—institutional theory. We utilized a database of 188 sport-related institutional studies and conducted a citation network analysis of the aggregated reference lists from these articles. We argue that the fields of management and sport management act like “ships in the night.” That is, as the field of sport management has become more distinctive, the field is becoming less connected with general management literature and contemporary theoretical discussions. Potential implications for sport management scholarship and understanding the nature of the field are discussed, along with how it may be possible (if desired) to bridge the gap between sport and management research.
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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 | 0.006 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.017 | 0.031 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".