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Record W4239470597 · doi:10.29173/cmplct22992

It's About Time

2014· article· en· W4239470597 on OpenAlexvenueno aff
Julie Vu, Sherrie Reynolds

Bibliographic record

VenueComplicity An International Journal of Complexity and Education · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

There is a way that people walk when they have walked a lot in hot weather.Their stride is deliberate, slow, loose-jointed, and sometimes includes an improvised shade of an umbrella, cap, scarf, newspaper, or even a piece of cardboard.There is something to be said for just starting out toward a place with no itinerary specifying when to be where or how long it should take.It is this kind of easy amble that allowed me to see a lizard lurking behind a cactus and decide to sit and watch it for a while before continuing on my journey.It is this kind of walking that too many American children, after being in a school where the whole day is spent moving mechanically between periods through stark hallways each day, would probably not recognize and, perhaps, would not even value.The experience of walking in the deserts of Arizona that Sherrie enjoyed as a child competes with traditional conceptions of time as a variable that can be controlled and manipulated.In his essay, A Postmodern Vision of Time and Learning, Patrick Slattery (1995) argues that modernist assumptions about "time marching forward in an irreversible trajectory" have evolved from the Newtonian vision of a clockwork universe (p.613).This exaggerated emphasis on time as an autonomous, quantifiable variable, Slattery contends, "can be traced to the assumption that the universe was created in time and space, as opposed to time and space being interwoven into the very essence of the cosmos" (p.613).Slattery indicts modern conceptions of time that present temporality as something that can be "controlled, managed, or manipulated for the purposes of advancing instructional objectives, improving classroom management, and enhancing evaluative results" (p.612).While such a linear conception of time dominates many contemporary pedagogical spaces, this practice may be especially egregious when it perpetuates increasingly narrow measures of achievement that fail to honor the web of cultural

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)0.002
metaresearch head score (Gemma)0.008
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: Empirical · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0080.017
Scholarly communication0.0140.015
Open science0.0010.007
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0500.017

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 head0.064
GPT teacher head0.314
Teacher spread0.250 · 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
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
Published2014
Admission routes1
Has abstractyes

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