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Record W2158064748 · doi:10.1177/0741088303260691

Tasks, Ensembles, and Activity

2003· article· en· W2158064748 on OpenAlexaff
Robert J. Bracewell, Stephen P. Witte

Bibliographic record

VenueWritten Communication · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsMcGill University
Fundersnot available
KeywordsComplementarity (molecular biology)Perspective (graphical)Activity theoryEpistemologySociologyLiteracyField (mathematics)Task (project management)Computer sciencePoint (geometry)Cognitive sciencePsychologyPedagogyArtificial intelligenceEngineeringMathematics

Abstract

fetched live from OpenAlex

This article is concerned with characterizing literacy activity as it is practiced in professional workplaces. Its starting point is activity theory, which grew out of the work of Vygotsky and has been subsequently elaborated in Russia and elsewhere. First, the authors propose that existing versions of activity theory are unable to account adequately for practical human activity in contemporary workplaces, and present a revised perspective that opens the way for new theoretical developments. Second, they elaborate two new constructs, task and work ensemble, and apply them to a short collaborative writing sequence collected in the field. Both constructs are seen to account in a substantive way for the structure of the composing activity carried out by the collaborators. They close with a discussion of the complementarity and theoretical advantages of the two constructs.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.006
Scholarly communication0.0040.005
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.089
GPT teacher head0.404
Teacher spread0.316 · 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 designQualitative
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

Citations43
Published2003
Admission routes1
Has abstractyes

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