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Record W2772945850 · doi:10.22329/il.v37i4.4794

Critical Thinking, Bias and Feminist Philosophy: Building a Better Framework through Collaboration

2017· article· en· W2772945850 on OpenAlexvenueno aff
Adam Dalgleish, Patrick Girard, Maree Davies

Bibliographic record

VenueInformal Logic · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsEpistemologyCritical thinkingSociologyFeminist philosophyFeminist epistemologyContext (archaeology)Argumentation theoryPhilosophy

Abstract

fetched live from OpenAlex

In the late 20th century theorists within the radical feminist tradition such as Haraway (1988) highlighted the impossibility of separating knowledge from knowers, grounding firmly the idea that embodied bias can and does make its way into argument. Along a similar vein, Moulton (1983) exposed a gendered theme within critical thinking that casts the feminine as toxic ‘unreason’ and the ideal knower as distinctly masculine; framing critical thinking as a method of masculine knowers fighting off feminine ‘unreason’. Theorists such as Burrow (2010) have picked up upon this tradition, exploring the ways in which this theme of overly masculine, or ‘adversarial’, argumentation is both unnecessary and serves as an ineffective base for obtaining truth. Rooney (2010) further highlighted how this unnecessarily gendered context results in argumentative double binds for women, undermining their authority and stifling much-needed diversity within philosophy as a discipline.These are damning charges that warrant a response within critical thinking frameworks. We suggest that the broader critical thinking literature, primarily that found within contexts of critical pedagogy and dispositional schools, can and should be harnessed within the critical thinking literature to bridge the gap between classical and feminist thinkers. We highlight several methods by which philosophy can retain the functionality of critical thinking while mitigating the obstacles presented by feminist critics and highlight how the adoption of such methods not only improves critical thinking, but is also beneficial to philosophy, philosophers and feminists alike.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
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 head0.086
GPT teacher head0.406
Teacher spread0.320 · 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.

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

Citations3
Published2017
Admission routes1
Has abstractyes

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