Social Networks Analysis in Accounting and Finance*
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.
Full frame distilled prediction
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.
- Candidate categories
- Meta-epidemiology (narrow), Science and technology studies, Scholarly communication
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: ObservationalConsensus signal: none
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.539
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.259 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
ABSTRACT Social network analysis (SNA) examines whether interactions between individuals, teams, and organizations result in network structures and patterns that can explain important outcomes, including firm performance, management reporting behaviors, investor beliefs, and audit outcomes. This paper reviews the growing body of work on SNA in accounting and finance research, focusing on 162 articles published between 2000 and 2021, and offers a roadmap that may help move this literature forward. Our survey summarizes the elements of SNA, organizes this literature within a theoretical framework, and provides a thematic discussion of the context and contribution of the selected studies. We also discuss opportunities and challenges for future research. Finally, we include an empirical illustration of the key concepts and tools of SNA. We believe that SNA will continue to offer an interesting avenue for conducting high‐impact and cross‐disciplinary research in accounting and finance.
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.
The record
- Venue
- Contemporary Accounting Research
- Topic
- Auditing, Earnings Management, Governance
- Field
- Business, Management and Accounting
- Canadian institutions
- not available
- Funders
- not available
- Keywords
- AuditAccountingContext (archaeology)Social network analysisSocial accountingAccounting researchWork (physics)BusinessFinanceManagement accountingSociologySocial capitalEngineeringSocial science
- Has abstract in OpenAlex
- yes