CORPORATE REBRANDING AS A MANAGEMENT STRATEGY FOR BRAND IMAGE IN THE UNIVERSITY
Bibliographic record
Abstract
Every University is unique in terms of profile, organizational structure, organizational culture, developmental stages, resources availability, politics, strategic goals, different faculties and other different issues.It is expected that the Management of Universities create a social, friendly and academic atmosphere that will enhance the interplay between the Management and other stakeholders in the building of a formidable corporate brand.Unfortunately, when multiple crisis happens, the Management of University reputation is at stake.Hence, the need for rebranding.This paper theorizes the effects of corporate rebranding on brand image in Lagos State University from a social constructionist point of view.With the aid of taxonomy of brand perspectives and the theory of Social construction, this paper was able to analyze labor relations, Management policies and brand image to conclude that continuous communication of information to stakeholders via formal and informal signals is very vital in creating formidable corporate brand image.Also, improved service quality and good public relations are very important for the development and management of University brand image.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".