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Record W4409324357 · doi:10.1080/13698230.2025.2489245

Mutual engagement as methodology: Joseph Carens and the ‘Toronto School’ of Political Theory

2025· article· en· W4409324357 on OpenAlexaffabout
Kiran Banerjee, Abraham Singer

Bibliographic record

VenueCritical Review of International Social and Political Philosophy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPoliticsSociologyEpistemologyPolitical philosophyPolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

Political theory and political philosophy are marked by a wide variety of approaches, which can be grouped broadly into normative/prescriptive, historical, and critical traditions of political thought. These are not just distinct in terms of scholarly focus, but also in methods, standards for evaluation, informal networks, conferences, and journals. Many scholars spend their graduate school years and much of their careers largely engaged in one or another of these fields, leading to a fractionalization of political theory. This contribution offers a conceptual framework for better understanding their interrelated nature, seeing these distinct fields as part of a common project of political theorizing. We call this framework ‘The Toronto School,’ named after a class Carens taught for graduate students at the University of Toronto. The Toronto School is less a particular method for doing political theory (the way, say, Skinner or Foucault offers) and more an ecumenical understanding of political theory as a discipline, which sees the various approaches and aims of our field as having unique and complementing competencies and blindspots that fit into a more general project of intellectual inquiry. This contribution articulates the broad contours of the Toronto School, with a particular eye toward the way it reconciles normative, historical, and critical approaches.

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)0.002
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
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 score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.007
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.072
GPT teacher head0.410
Teacher spread0.338 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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