Technology Management: A Cross-Disciplinary Master-Program with a Focus on Leadership
Bibliographic record
Abstract
Leadership is important. Management is important. There are good reasons to conceptually and pedagogically separate the two in order to see some fundamental differences. In a cross disciplinary master program named Technology Management at Lund University, Sweden, the students are given opportunities to study and learn management, and however, what makes the program unique is its profound focus on leadership. The Technology Management program includes six courses, Teamwork and Leadership being one of them. In this course, theories and knowledge in leadership is learnt and discussed, this is then intertwined into the other courses in which it is practiced, and finally the outcome is brought back to the Teamwork and Leadership course for further discussions. In addition to this the students are writing daily reflections in a so called Learning Journal, over a one-year period, making it possible for the students to reflect over and thereby shape their own leadership style and mindset. Course evaluations and placement reports indicates that the students learning about theories, practice and mindset related to leadership is ranked as the most valuable learning from their entire educational curricula/period.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.068 | 0.026 |
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".