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A Social Media Platform to Advance Critical Management Education and the Mode 3 University

2024· article· en· W4400439995 on OpenAlexaff
Amy Zidulka

Bibliographic record

VenueAcademy of Management Proceedings · 2024
Typearticle
Languageen
FieldComputer Science
TopicEducation and Learning Interventions
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsSocial mediaMode (computer interface)SociologyComputer scienceEngineering managementEngineeringWorld Wide WebHuman–computer interaction

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.326
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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