From licence to operate to licence to lead: A case study of 7-Eleven Canada's corporate legitimacy and reputation
Bibliographic record
Abstract
This case study investigates 7-Eleven Canada’s corporate legitimacy and reputation as perceived by key provincial government regulators in gaming and tobacco control, and healthy food promotion. Measuring corporate legitimacy as a springboard for reputation has been a challenge for reputation scholars. Building on King and Whetten (2008), this case study finds that deficient legitimacy on regulatory compliance did not prevent 7-Eleven from building favourable reputation on elevated compliance measures. Regulators awarded 7-Eleven an above-average reputation that mirrored the reputation of the convenience store industry in a competitive retail environment. As part of a corporate reputation management plan for 7-Eleven, citizenship-building initiatives are highlighted to close the reputation gaps uncovered in the case study. The research method was modelled on the Harris/Fombrun Reputation Quotient. Further research could test the proposition that corporate legitimacy and reputation can operate as seemingly semi-detached concepts.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".