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Record W4384704635 · doi:10.7202/1099902ar

Habermasian Discourse Theory for Educational Policymaking: Attending to Perspective Taking and Communicative Agency

2023· article· en· W4384704635 on OpenAlexaffvenue
Darron Kelly

Bibliographic record

VenuePhilosophical Inquiry in Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCommunicative actionConceptualizationAgency (philosophy)NormativeEpistemologySociologyPerspective (graphical)Context (archaeology)Discourse analysisValue (mathematics)Social scienceLinguistics

Abstract

fetched live from OpenAlex

This paper identifies and considers issues of perspective taking and communicative agency in applying Jürgen Habermas’s discourse theory to policymaking in educational settings. The central question is whether Habermas provides an epistemic framework that supports reciprocal and sincere expressions of the views and interests of individuals in a heterogeneous society. Examining this question leads to a discussion of “practical discourse” in light of a willingness of participants to reach mutual understanding and agreement, and the centrality of perspective taking and communicative agency in such discourses. Also examined is a conceptualization of “application discourses,” the implications of such discourses for perspective taking and communicative agency, and the role these discourses might play in further assuring the overall inclusivity and context sensitivity of applying education policies in specific circumstances. The paper then gives a brief re-analysis of an empirical study that used Habermas’s concept of the “ideal speech situation” as a normative framework for interpreting data. The re-analysis means to illustrate the practical value of practical discourse for guiding and assessing educational policymaking. The paper ends with a short justification of the necessity of attending to perspective taking and communicative agency when viewing education as a basic human right.

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)0.003
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 score0.795
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.343
GPT teacher head0.542
Teacher spread0.199 · 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
Published2023
Admission routes2
Has abstractyes

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