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Theorizing Profound Change in Bourdieu's Framework: Communities of Practice as Developing Fields

2017· article· en· W2766400165 on OpenAlexaff
Thierry Gateau, Laurent-Mehdi Chokri, Filippo Furri

Bibliographic record

VenueAcademy of Management Proceedings · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsHabitusSituatedTransformative learningSociologyCommunity of practiceInstitutionalisationPractice theoryIdentity (music)Field (mathematics)NegotiationSituated learningEpistemologyPower (physics)Perspective (graphical)PedagogyPolitical scienceSocial scienceCultural capitalComputer science

Abstract

fetched live from OpenAlex

Building on the theory of the field’s tension between structure and individual behavior, reproduction and change, we try to identify and follow the mechanisms behind the emergence of alternative practices. Situated learning and community of practice (Lave & Wenger, 1991; Brown & Duguid, 1991; Wenger, 1998) seems to open a path to approach this question alongside other recent works (Landley et al., 200; Mutch, 2003; Huzzard, 2004) suggesting power is a key concept to understand transformative dynamics. Dominating structures challenge the stability of communities, so do the presence of outsiders carrying their antecedents, struggling and negotiating transferable component of identity. In this regard, we seek to highlight that some communities of practice and their interactions with outer communities, in a wider perspective, can act like triggers and create new fields or subfields. They are “protofields”, social entities we describe as a community bounded by an emerging habitus. We suggest that integrating the Bourdieu’s framework to situated learning theory and community of practice provide a tool to understand the construction, evolution and institutionalization of alternative practices.

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)0.001
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: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.085
GPT teacher head0.417
Teacher spread0.332 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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