The future of interpretive accounting research
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.
Bibliographic record
Abstract
Purpose The purpose of this paper is to contribute to the polyphonic debate on the future of interpretive accounting research (IAR) by addressing the issues of cumulative knowledge and embedment of IAR in wider literatures. Design/methodology/approach McCracken's method of inquiry, adapted to incorporate meso‐level considerations, can be used to help resolve these issues. Accounting‐related phenomena can be studied by first identifying the cumulative knowledge contributed by different theoretical perspectives that provides broad skeletal categories to be investigated in the context of an interpretive study. In addition, micro‐ and macro‐level “external” theories are incorporated in a global meso‐level framework to provide a high‐level lens to guide data generation and analysis, fostering the embedment of IAR in wider literatures. Findings Meso‐level research implies thinking organizationally and behaviourally, and thinking about linkage. By extension, it requires reflecting on the characteristics of the context in which the phenomenon occurs and the actors behave, the nature of the task or decision to perform, and possible links between macro‐ and micro‐factors that help identify “external” theories and frameworks that contribute to understanding the phenomenon. Research limitations/implications The contribution of the suggested approach is highlighted in the context of financial accounting research. Reflexive accounts on the choice and use of a meso‐level approach are presented, and the issue of appropriate balance between theoretical and empirical material is addressed. Originality/value Creativity is fostered when cumulative knowledge about a specific phenomenon is embedded in wider meso‐level theoretical perspectives, leading to the discovery of new insights about the topic under study and contributing to the advancement of knowledge.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
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