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Record W7014183175

A Pedagogy of Discomfort: A Qualified Defense

2018· dissertation· en· W7014183175 on OpenAlexafffund

Bibliographic record

VenueQSpace (Queen's University Library) · 2018
Typedissertation
Languageen
FieldSocial Sciences
TopicEducational Philosophies and Pedagogies
Canadian institutionsQueen's University
FundersQueen's University
KeywordsSubject (documents)Circumstantial evidenceProcess (computing)Work (physics)PretextFrame (networking)
DOInot available

Abstract

fetched live from OpenAlex

This thesis considers Megan Boler’s proposal for a pedagogy of discomfort, an approach to social justice education that harnesses students’ emotional responses of felt discomfort, such as anger or guilt, in order to prompt them to critically interrogate their existing beliefs, assumptions, and ways of seeing. Upon highlighting critiques of politicized curricula, I consider one potential objection that may be levelled against a pedagogy of discomfort, namely, that this pedagogy constitutes an imposition on students by the educator, infringing on students’ freedom to hold certain beliefs, assumptions, and ways of seeing. I argue that in cases where the would-be participants in a pedagogy of discomfort are the beneficiaries of the particular unjust social structure under scrutiny, this imposition is justified as a lesser evil. I then address some of the challenges that may arise from implementing a pedagogy of discomfort in classrooms in which some individuals are harmed by the particular unjust social structure under scrutiny. I suggest that two tensions arise from imposing this pedagogy on these individuals. First, subjecting these individuals to the process of critical inquiry appears to reproduce the conditions whereby they are denied status as epistemic agents. Second, the act of collective witnessing through which the process of critical inquiry takes place requires that all participants recognize one another as epistemic agents. However, I argue that this mutual recognition may not be present in classrooms in which some individuals are harmed by the particular unjust social structure under scrutiny. I argue that the presence of these two tensions gives reason for caution when imposing a pedagogy of discomfort on students who are harmed by the particular unjust social structure under scrutiny.

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)0.014
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0090.079
Scholarly communication0.0120.020
Open science0.0040.019
Research integrity0.0130.025
Insufficient payload (model declined to judge)0.0090.002

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 head0.026
GPT teacher head0.305
Teacher spread0.279 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2018
Admission routes2
Has abstractyes

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