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Record W4220748240 · doi:10.30828/real.951165

Student Leadership and Student Government

2022· article· en· W4220748240 on OpenAlexafffund
Justin Patrick

Bibliographic record

VenueResearch in Educational Administration & Leadership · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsTokenismPoliticsScholarshipPolitical scienceGovernment (linguistics)Leadership stylePower (physics)Educational leadershipPublic relationsServant leadershipLeadershipPedagogyStudent affairsDemocracyAction (physics)Higher educationSociologyLaw

Abstract

fetched live from OpenAlex

Student leadership is often misconceptualized as merely a pedagogical exercise revolving around simulated political arenas with little to no immediate real political consequence. Other scholarship normalizes students as political outsiders who have to resort to dangerous, exhausting activism tactics for even minute advocacy victories due to their lack of structural representation in education decision-making. An analysis of student leadership in research and practice is presented according to an identified spectrum of low to high student power. This article argues that student leadership has great potential for real political action. The best structure for student leadership is argued to be democratic student government, as well as students having standing roles within education leadership structures. Furthermore, effective conceptions of student leadership must not only acknowledge its developmental aspects, but also account for the real politics inherent in student leadership activities. To conclude, a more political conception of student leadership and student government is advocated for so student leaders’ real political activities can be recognized and studied as such in education leadership discourse to prevent student exploitation and tokenism.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.009
Scholarly communication0.0070.002
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.457
GPT teacher head0.517
Teacher spread0.060 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations15
Published2022
Admission routes2
Has abstractyes

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