I Despise Them! I Detest Them! Franchise Relocation and the Expanded Model of Organizational Identification
Bibliographic record
Abstract
When it comes to fans of professional sport teams who are left behind when their favorite team relocates to a new city, the authors argue that there are a variety of ways in which these fans can identify with the relocated team. This runs against the traditional conception of how left-behind fans view the franchise in its new home. Fans are thought to follow two paths: They either cheer for the team in the new city, or they stop cheering for the team altogether. The authors have found that this conception of fans is inadequate. Using the expanded model of organizational identification (EMOI), the authors find that after a team relocates there are at least five different ways a fan can identify with the relocated team: identification, disidentification, schizoidentification, neutral identification, and nonidentification. These are illustrated by fitting the stories of 23 Hartford Whalers fans into the model.
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How this classification was reachedexpand
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".