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Record W2142451525 · doi:10.29173/cmplct8724

Classrooms Can Use Therapy Too

2005· article· en· W2142451525 on OpenAlexvenueno aff
Elizabeth D. Burris

Bibliographic record

VenueComplicity An International Journal of Complexity and Education · 2005
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsObjectivismFamily therapyDeterminismEpistemologyPsychologyCoherence (philosophical gambling strategy)Control (management)PedagogyComputer sciencePsychotherapistPhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

Paul Dell, a family systems therapist inspired by the systems thinking of Humberto Maturana, posits that family systems achieve pathology because of what he calls “epistemological errors”: either the refusal to acknowledge reality or the desire to control reality. Reality, in Dell’s definition, is the coupled nature of human interaction, or structure determinism. Applying Dell’s definition to classrooms, I identify two epistemological errors commonly committed by teachers: valuing content more highly than relationships in the classroom and attempting to control students through classroom management techniques. When these two practices are viewed through the systems lens rather than through the modernist, objectivist lens, the relationships that are enacted in a classroom among teacher, students, and the content under study come into focus, and pathology, or repetitive behaviors that obviate desired learning, is more easily discerned. Given the emphasis systems theory places on relationships, I claim that, as with family systems, classroom systems can benefit from the kind of analysis—or “therapy”—that exposes the “coherence,” or the tight relational couplings, within the system that, in some cases, invites non-educative interactions. Such therapy can help teachers shift their own attitudes and behaviors so as to influence those of their students.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.106
GPT teacher head0.380
Teacher spread0.274 · 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 designObservational
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

Citations12
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueComplicity An International Journal of Complexity and EducationSame topicCounseling, Therapy, and Family DynamicsFrench-language works237,207