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Record W1790191735 · doi:10.1016/j.aos.2015.07.002

Twittering change: The institutional work of domain change in accounting expertise

2015· article· en· W1790191735 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAccounting Organizations and Society · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversity of WaterlooUniversity of Victoria
Fundersnot available
KeywordsDomain (mathematical analysis)Work (physics)Rhetorical questionAccountingPublic relationsSocial mediaSociologyKnowledge managementPolitical scienceBusinessComputer scienceEngineeringWorld Wide Web

Abstract

fetched live from OpenAlex

This paper develops an endogenous model of institutional and professional domain change. Traditional accounts of domain change focus attention on how professional expertise is extended to new areas of practice. This form of domain extension is typically both deliberate and contested. However, domain change can also occur in a somewhat quotidian and uncontested fashion when professional expertise is extended intra-organizationally. We analyze the ways in which the domain of accounting expertise is reconstituted in new social media – Facebook, LinkedIn and Twitter – in Big 4 accounting firms. Using content analysis and interview data we show how social media professionals, in pursuing their own professional project, generate change in the professional domain of accountancy. Our analysis demonstrates that the institutional work of domain change occurs through three related activities: boundary work, rhetorical work and the construction of the embedded actor.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.038
GPT teacher head0.239
Teacher spread0.201 · 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