Thinking Outside the Box – Eliminating the Perniciousness of Box‐Ticking in the New Corporate Governance Code
Bibliographic record
Abstract
Abstract On 16 July 2018, a new corporate governance code was published. Like previous iterations, it applies on a ‘comply‐or‐explain’ basis, whereby companies are required to either comply with provisions or explain reasons for non‐compliance. However, the new code substantially simplified the previous version of the code in an attempt to attenuate the process of ‘box‐ticking’. Box‐ticking manifests itself firstly, by companies complying with the letter rather than the spirit of the provisions, and, second, by companies not utilising the inherent flexibility of the code to implement their optimum firm‐specific governance structures by explaining rather than complying. This article elucidates the history of box‐ticking, and the reasons why companies succumb to it, since Adrian Cadbury pioneered the concept of ‘comply‐or‐explain’ in 1992, before proposing an exclusively principles‐driven approach to the corporate governance code which would alleviate box‐ticking and fulfill the original aspirations of Cadbury over a quarter of a century ago.
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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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.028 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".