A Social Media Platform to Advance Critical Management Education and the Mode 3 University
Bibliographic record
Abstract
The term “mode 3 university”— what Barnett (2017) has called “the ecological university” and Nørgård, Mor, and Bengtsen (2019) the “networking university”—has been employed to describe a reimagination of the university as an institution that is more entangled with the world outside its walls. This paper contextualizes Critical Management Education (CME) scholarship that champions further engagement with the world as aligned with the mode 3 vision and advocates for realizing this vision via a university owned and managed social media platform. The platform would be a space of connection between students, faculty, staff, and the broader world. It would blur boundaries between formal and informal learning and between the social, civic, and academic spheres. The university’s identity would shift from its current identity as a provider of classes to being a site of learning and community. Social media would not be the only means by which such connection would happen but would be a central enabler. While formal classes would remain important, they would be decentred as the dominant sites of learning. This paper contributes to CME by advancing a critical process pedagogy that advocates for out-of-class engagement. It further contributes by drawing links between CME and scholarship from outside the discipline of management that explores critically informed post-digital pedagogies, and specifically how social media’s conduciveness to self-directed informal learning, democratic co-creation of knowledge, and collective organizing might be leveraged to serve emancipatory ends.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".