Using Implicit Followership Theories to Illustrate Cognitive Schemas: An Experiential Exercise
Why this work is in the frame
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Bibliographic record
Abstract
In this article, we outline an experiential exercise designed to teach students about cognitive schemas (what they are, how they are developed, and how they may influence us). Drawing on the literature related to implicit followership theories, the exercise encourages students to explore their perceptions related to the role of followers, thus providing a concrete example via which they can explore the concept of schemas. The exercise was designed in the context of an undergraduate organizational behavior course and has been used on four occasions with success. We describe the learning objectives of the exercise and the steps to run it, provide detailed instructor notes, and offer some supplementary materials (i.e., sample content for class slides). We conclude the article by proposing potential variations of the exercise.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 0.001 |
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