Business unit controllers' credibility and the hardening of local forecasts
Bibliographic record
Abstract
Abstract Focusing on multidivisional companies, this paper analyzes the hardening of local forecasts at the intersection of business units (BUs) and the corporate finance function. It investigates how BU controllers, accountable to both local management and the corporate finance function, seek to establish themselves as competent and trustworthy forecasters vis‐à‐vis their functional superiors. Drawing on Goffman's dramaturgical sociology, we demonstrate how these encounters constitute episodes in a multiperiod hardening game feeding into the management of forecast quality and anticipatory control. We illustrate how expressive performances of their competence and trustworthiness are vital for BU controllers to manage vertical information flows between the local and the corporate level and for aligning corresponding interests. Convincing performances can reinforce BU controllers' status as stewards of the forecasting process and help to maintain a “truce” between the local and the corporate level, assuring corporate controllers that the unit's future is under control.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".