Getting Back to Basics: Challenging Complexity and Accountability in the Boardroom
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
This paper investigates the dynamics of complexity and expertise in the context of compensation committees (ccs). Drawing on semi-structured interviews, mostly with cc members and consultants, we bring to light two axes of subordination that impact the mindset of corporate governance participants, and may ultimately undermine directors’ degree of accountability to shareholders. The first axis involves cc members’ subordination to consultant expertise, which tends to be considered as an indispensable ally in dealing appropriately with the webs of complexity that allegedly characterize executive compensation. Nourished partially by the first axis, the second implies subservience to these webs of complexity, which are widely presumed and naturalized by cc members and the consulting experts they employ. One of our main contributory statements is to question the ascendancy of complexity in the boardroom, casting doubt on one of the key assumptions upon which practices and expertise in contemporary corporate governance institutions are built and promoted. We also question the extent of epistemic dependency in many compensation committees, where much of the knowledge necessary to properly operate the repertoire of practices (deemed necessary to address the problem of executive compensation determination) is not primarily in the hands of cc members, but rather in those of consultants.
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 | 0.001 |
| 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 it