Branding higher education: an exploration of the role of internal branding on middle management in a university rebrand
Bibliographic record
Abstract
Abstract Although research on branding in higher education has grown, a specific focus on internal branding in this sector is still scarce. Brand support by mid-level administrative staff and deans is a key element in internal branding of a university. This study explores the extent to which internal branding contributes to this group’s understanding of and engagement with a public institution’s rebranding campaign. It identifies challenges and practice insights for practice for internal branding activities when engaging these internal stakeholders, linking to wider brand management theory and practice. A qualitative case study approach was employed to understand the effectiveness of internal branding holistically, and in context. In 2016, nineteen depth interviews were conducted with a range of mid-level administrators and deans including those at the student union, regional campuses, directors of departments, and deans of faculties and schools at a large Canadian university. The data was analysed using Nvivo qualitative data analysis software. On the basis of the results, it is apparent that internal branding has a valuable role in relation to higher education brand management strategy. Results offer a holistic view of the rebranding process, and explore understanding of and engagement with the rebranding campaign. This paper addresses a gap in the public sector brand management literature and demonstrates theoretical and practical implications for improved understanding and brand management strategy.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".