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Materializing Practices: When Elusive Social Practices Meet Digitization

2015· article· en· W2464657168 on OpenAlexaff
Bijan Azad, Samer Faraj

Bibliographic record

VenueAcademy of Management Proceedings · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInformation Systems Theories and Implementation
Canadian institutionsMcGill University
Fundersnot available
KeywordsMateriality (auditing)Assemblage (archaeology)DigitizationExtant taxonTemporalitiesSociologyElement (criminal law)AestheticsEpistemologyEnvironmental ethicsPolitical scienceHistoryArchaeologyEngineeringArtLawPhilosophy

Abstract

fetched live from OpenAlex

With the increasing scholarly interest in the materiality of organizing, the ontological separateness between the social and the material remains problematic. However, little progress has been achieved exploring the role of materiality to the very enactment (existence) of work practices. We address this question via a field study of a large project involving technology-derived change in a governmental agency. Our study posed two interrelated research questions: What is the role of materiality in the enactment of practices? And why does materiality matter for some practices more than others? We found that transformation of elusive practices at a time of technological change is dependent on a) rebuilding the linkages that tie together the sociomaterial assemblage, b) reshaping intelligibility for the participants, and c) evolving new work arrangements that are negotiated by the stakeholders. By tracing in great detail the evolution of three specific practices, we contribute to a more thoroughly materialized account of transformation, emergence and disappearance of practices within the extant literature. Specifically, in explaining the role of the material in evolving practices we highlight how our conception of assemblage can capture the spirit of materializing process during sociomaterial change. That is, if changes in the material element are accompanied by relative continuity in other elements of the assemblage then the practice is likely to morph by maintaining significant family resemblance between old and new--elements of the practice may survive albeit through re-combination or mutation. Furthermore, if the changes in the material element are vast and wholesale, there is likely to be total breakdown of intelligibility and the old practice is likely to be rendered defunct.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.855
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.005
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 head0.156
GPT teacher head0.420
Teacher spread0.265 · 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
Published2015
Admission routes1
Has abstractyes

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