A privatization success story: accounting and narrative expression over time
Bibliographic record
Abstract
Purpose This paper is the third in a trilogy of papers to explore the use of accounting as a fundamental element in senior management's narrative regarding the privatization of a major transportation enterprise, Canadian National Railway (CN). The paper aims to examine how two accounting performance benchmarks (the operating ratio, and free cash flow) were deployed to help sustain a rhetoric of post‐privatization success. The aptness (and the danger) of accounting language in strategic narrative is highlighted. Design/methodology/approach The paper describes the importance of senior management discourse in the aftermath of a privatization. A narrative perspective is adopted, in which an imagined future post‐privatization era initially articulated in accounting language is then told and re‐told as the post‐privatization years unfold. Accounting performance measures highlighted in the story of success of the privatization in the Annual Letters to Shareholders by the CEOs of CN in the ten years following privatization in 1995, and celebrated in the Annual Report, are examined critically. Findings The results emphasize the important features and role of accounting language and accounting‐based performance benchmark measures in the narrative construction of the success of a privatization by corporate leaders. Research limitations/implications Case studies possess the strength of specific instance detail and interpretation, and the ostensible weakness of interpretation of a sample of one. But such research can provide for a reframing of conceptual perspectives and stimulate additional efforts to interrogate the role of accounting language in events of major social change. Practical implications The paper strongly endorses the adoption of a critical analytical perspective by those affected by a major social change (such as a privatization) in which the role of accounting language is subtle, but nonetheless persuasive and enduring. Originality/value The paper examines a case study in which the narrative framing of success is made rhetorically potent by deploying accounting performance measures. The paper reinforces the view that accounting is not an innocent bystander in the political and narrative manoeuvrings associated with a privatization. Accounting does not axiomatically provide an objective measure of some underlying financial truth, but is part of an arsenal of rhetoric to achieve political ends.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.019 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".