The role of trust in creating value and student loyalty in relational exchanges between higher education institutions and their students
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The globalization of educational services and the increasing competition coming from the private sector have forced higher education institutions to market their programs more aggressively and to look at student loyalty as the key for future success. Student loyalty to higher education institutions represents not only a more stable financial basis for such institutions but also continuing support for them after graduation. The present research examines the relational exchange process between higher education institutions and their students. Specifically, it explores the process by which trust is first developed and then translated into students' perceived value of the higher education institutions, ultimately leading to the development of student loyalty toward those institutions. The identification of the components and the outcomes of student trust are presented on the basis of Sirdeshmukh, Singh, and Sabol's trust–value–loyalty framework.
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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 | 0.001 |
| 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 it