Logics Multiplicity and Accounting Adaptiveness in Response to Sustainability Emergence: A Single Case Study from a Canadian University
Bibliographic record
Abstract
For the last few decades, accounting scholars have established that accounting is a complex practice because of the confluence of social, cultural, political, and global aspects. Accounting is viewed as an enabling vehicle to reflect multiple logics. There is still a dearth of research exploring in-depth how the accounting practices of an organization adapt to the interplay between multiple logics in the context of a newly emerged logic. This study explored how the sustainability-infused rules and routinization process have changed in response to extant (such as governance logic, professionalism, managerialism, and state logic) and newly emerged (sustainability) logics in a higher education institution. \nThis study draws on the institutional logics perspective and employs this theoretical perspective in a single case study (a mid-sized Ontarian research university) that recently has recognized sustainability as one of the strategic pillars. Data were collected for various departments and units using multiple data collection methods: semi-structured interviews, internal documents, and publicly available documents. The findings suggest that the accounting practice of the sample case study started to adapt, mainly in an informal way, to incorporate some sustainability concerns into its rules and routinization process. Accounting practice is influenced by state logic and managerialism and sometimes creates a competing manifestation with sustainability logic. The study will contribute to the literature by unpacking the malleable nature of accounting by showing sustainability-infused accounting evolution in a multi-logic organizational atmosphere. The interplay between extant and emerging logics informs the role of institutional logics in sustainability-focused accounting evolution and, thus, contributes to both accounting and sustainability literature. Although many higher education institutes have embarked on sustainability, no research has been offered to establish sustainability as a logic in the higher education sector. To fill this gap in the extant literature, this paper is one of the early attempts to offer sustainability as an emerging logic in the higher education sector. The study concentrated on exploring accounting adaptiveness due to energy saving and responsible investment initiatives, as these were the areas in which ONUNIV made early responses to sustainability.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".