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Record W4313365849 · doi:10.1108/qram-09-2022-0135

The future of public sector accounting research. A polyphonic debate

2022· article· en· W4313365849 on OpenAlexaff
Giuseppe Grossi, Ileana Steccolini, Pawan Adhikari, Judy Brown, Mark Christensen, Carolyn Cordery, Laurence Ferry, Philippe Lassou, Bruce D. McDonald, Ringa Raudla, Mariafrancesca Sicilia, Eija Vinnari

Bibliographic record

VenueQualitative Research in Accounting & Management · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsOriginalityPolyphonyHybriditySociologyScholarshipPluralism (philosophy)Accounting researchPublic sectorConversationValue (mathematics)ReflexivityContext (archaeology)Engineering ethicsEpistemologySocial scienceAccountingPolitical scienceQualitative researchEconomicsPedagogyEngineeringLawComputer science

Abstract

fetched live from OpenAlex

Purpose The purpose of this polyphonic paper is to report on interdisciplinary discussions on the state-of-the-art and future of public sector accounting research (PSAR). The authors hope to enliven the debates of the past and future developments in terms of context, themes, theories, methods and impacts in the field of PSAR by the exchanges they include here. Design/methodology/approach This polyphonic paper adopts an interdisciplinary approach. It brings into conversation ideas, views and approaches of several scholars on the actual and future developments of PSAR in various contexts, and explores potential implications. Findings This paper has brought together scholars from a plurality of disciplines, research methods and geographical areas, showing at the same time several points of convergence on important future themes (such as accounting as a mean for public, accounting, hybridity and value pluralism) and enabling conditions (accounting capabilities, profession and digitalisation) for PSA scholarship and practice, and the richness of looking at them from a plurality of perspectives. Research limitations/implications Exploring these past and future developments opens up the potential for interesting theoretical insights. A much greater theoretical and practical reconsideration of PSAR will be fostered by the exchanges included here. Originality/value In setting out a future research agenda, this paper fosters theoretical and methodological pluralism in the interdisciplinary research community interested in PSAR in various contexts. The discussion perspectives presented in this paper constitute not only a basis for further research in this relevant accounting area on the role, status and developments of PSAR but also creative potential for practitioners to be more reflective on their practices and also intended and united outcomes of such 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 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)0.085
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.915
Threshold uncertainty score0.448

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0850.063
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.008
Science and technology studies0.0110.084
Scholarly communication0.0470.057
Open science0.0020.012
Research integrity0.0130.012
Insufficient payload (model declined to judge)0.0050.001

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 head0.308
GPT teacher head0.568
Teacher spread0.260 · 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.

Study designTheoretical or conceptual
DomainMethods
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

Citations76
Published2022
Admission routes1
Has abstractyes

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