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Record W2979951207 · doi:10.1111/faam.12219

Accounting change in the Scottish and Westminster central governments: A study of voice and legitimation

2019· article· en· W2979951207 on OpenAlexfundno aff
Noel Hyndman, Mariannuziata Liguori

Bibliographic record

VenueFinancial Accountability and Management · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsLegitimationRationalisationOrganisational changeVoiceGovernment (linguistics)Political scienceAccountingHorizontal and verticalPublic administrationPublic relationsBusinessPoliticsLawLinguisticsGeography

Abstract

fetched live from OpenAlex

Abstract Organisational voice processes are crucial during change. These will affect actors’ individual understanding of change and the way in which change is perceived and legitimated generally. Looking at accounting changes at two government levels (Westminster and Scotland), this paper explores relationships between organisational voice processes during change (exploring these in terms of horizontal/vertical and promotive/prohibitive dimensions) and legitimation strategies subsequently used by the actors involved. In Westminster, where promotive vertical voicing was particularly identifiable, interviewees predominantly legitimated change through rationalisation strategies. In Scotland, where prohibitive, horizontal voice processes were more evident, authorisation strategies tended to prevail. However, regardless of the content and direction of voice, ultimately, the vast majority of key accounting changes in both Westminster and Scotland were supported (legitimated) by actors.

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)0.005
metaresearch head score (Gemma)0.011
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.842

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0070.011
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.041
GPT teacher head0.347
Teacher spread0.307 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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