Use when situating an Accounting, Organizations and Society (AOS) manuscript in the literature — entering one of the journal's own long-running conversations, engaging the interdisciplinary sources (organization theory, sociology, psychology) those conversations draw on, and marking precisely what the paper adds. Positions the argument; it does not build the theory itself (aos-theory-development).
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AOS is unusual: half a century of its own archive defines the conversations it cares about, and its editors read submissions against that archive. Locate the specific AOS thread your paper extends:
| Thread (examples from the canon) | You must engage it if your paper is about… |
|---|---|
| Roles of accounting beyond the textbook — Burchell et al. (1980); Hopwood (1983) | any claim that accounting does unexpected work |
| Accounting, power and the calculable person — Miller & O'Leary (1987) | costing, performance measurement, discipline |
| Accountability in everyday organizational life — Roberts & Scapens (1985) | how systems shape conduct and self-accounts |
| Budgets as political instruments — Covaleski & Dirsmith (1986) | budgeting, resource struggles, institutional pressure |
| Numbers as inscriptions and constructed reality — Hines (1988); Robson (1992); Chua (1995) | measurement, representation, expertise |
| Culture change through accounting — Dent (1991) | field studies of transformation |
| Control systems and strategy — Simons (1990) | management control design in use |
| Behavioral/JDM synthesis — Libby, Bloomfield & Nelson (2002) | experimental financial-accounting work |
| Risk and audit society — Power (2009) | risk management, auditability, regulation |
(Full verified references: resources/exemplars/library.md.)
AOS conversations run on imported theory. Cite the primary social-science sources your tradition uses (e.g., the sociology behind institutional theory; Foucault for governmentality; Latour for inscriptions; the cognitive/social psychology behind a JDM design) as they are used in accounting — showing you know both the origin and the accounting appropriation. A paper that cites only accounting journals signals thin theorizing; one that cites only sociology signals the wrong venue.
【Thread】the AOS conversation entered; key papers ...
【Settled view】what that conversation currently believes ...
【Crack】the anomaly / silence / contradiction ...
【Delta】vs nearest papers 1 / 2 / 3 — one sentence each ...
【Interdisciplinary base】primary sources + their accounting appropriation ...
【Next step】aos-methods
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Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
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Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
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Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.
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Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.
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Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.
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Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.
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