The governance role of the board in corporate strategy: a comparison of board practices in 'for profit' and 'not for profit' organisations
Bibliographic record
Abstract
To what extent are there differences in the strategic practices of Boards of 'for profit' and 'not for profit' organisations? While there are obvious differences in the way these two types of organisations operate, the question as to whether those differences extend into the boardroom – and, especially, how directors engage with their managements on strategy – is currently unknown. Accordingly, this paper reports on the nature and extent of the board's strategic role in both for profit and not for profit organisations and then makes a direct comparison of them. Interestingly, the lack of significant differences between these two types of organisation constitutes the major finding of this current investigation and suggests that, in the area of governance, the supposed – or claimed – differences between for profit and not for profit organisations may be more imagined than real. In fact, there may be some very practical reasons for their similarity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".