IT and the Board of Directors: An Empirical Investigation into the “Governance Questions” Canadian Board Members Ask about IT
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT: In modern organizations, information technologies (IT) often help drive organizational strategies. As such, IT require both judicious planning and oversight. While executive oversight over IT is quite common nowadays, several studies indicate that due to the many benefits and risks associated with IT, more/better board-level oversight may be in order. Unfortunately, there is a scarcity of research on the involvement of board members in IT governance. We attempt to partially fill this gap by empirically examining the degree to which the 27 IT governance questions that make up an IT board governance framework recommended by the Canadian Institute of Chartered Accountants are raised by the board members of 94 Canadian firms. We also investigate the extent to which the questions are considered important. Our findings show that: board members use only some of the IT governance questions and not all the recommended ones; there is a gap between the IT governance questions board members ask and the ones they perceive to be important; and the number and importance of IT governance questions that board members ask appear to vary with both their organization’s strategic use of IT and the need for IT reliability. Implications for research and practice are offered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 0.006 |
| 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 it