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Record W2151917265 · doi:10.29173/cmplct8954

A review of "Complexity and Education: Inquiries into Learning, Teaching, and Research" by Brent Davis and Dennis Sumara, 2006

2010· review· en· W2151917265 on OpenAlexaffvenue
Randa Khattar, Carol Anne Wien

Bibliographic record

VenueComplicity An International Journal of Complexity and Education · 2010
Typereview
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsYork University
Fundersnot available
KeywordsMathematics educationPsychologyCognitive science

Abstract

fetched live from OpenAlex

Inquiries into Learning, Teaching, and Research is an insightful, clearly-written, and provocative contribution to the body of educational complexivist literature-an account we think particularly relevant for researchers and practitioners engaged in a transformative educational ethic.Evoking the phrase "more than human" (Abrams, 1996) as a sensibility where human concerns and action are nested within broader worlds of meaning, and the notion of knowing as adhering to a logic of adequacy, not optimality (a position Maturana and Varela (1998) also hold), Davis and Sumara present complexity thinking as a "pragmatics of transformation" (p.74) offering "explicit advice on how to work with, occasion, and affect complexity unities" (p.130).Davis and Sumara take care not to position complexity thinking as a "hybrid" seeking "common ground" (p.4) or a "metadiscourse" (p.7), but as a deeply complicit and participatory way of acting which might offer education itself as an "interdiscourse" (p.159), and simultaneously as a pragmatics with which to engage in the practical educational project.Davis and Sumara see complexity thinking as irreducible participation across multiple, interrelated systems of organization.They introduce the term level-jumping to describe knowing or learning as the capacity to participate in such a multiplicity of separate, yet inseparable, systems (e.g., biological, individual, social, evolutionary).We could quibble with the authors' use of the term level, one of those linear terms so embedded in everyday language, and which may easily suggest "higher" and "lower", or leaving one level behind while moving to another.Yet the authors' point is precisely that these levels or organizational systems are embedded in the action of learningsimultaneously interconnected and inseparable.What such terms render visible is the

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)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.014
Science and technology studies0.0010.003
Scholarly communication0.0040.007
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.002

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 head0.374
GPT teacher head0.557
Teacher spread0.183 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2010
Admission routes2
Has abstractyes

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