Intellectual capital governance and the knowledge economy in Canada
Bibliographic record
Abstract
Intellectual capital, as opposed to traditional conceptions of intellectual property, is neither as simple to define nor as straightforward to protect and regulate. As companies in the financial services sector attempt the efficient management of increasingly voluminous and strategically important information and knowledge, governance mechanisms currently available in the Canadian context have not kept pace. This thesis is at once a retrospective and prospective examination of the regulation and control of intellectual capital. The first two substantive sections of this thesis are primarily definitive and contextualizing---first defining the nature of contemporary legal and managerial concepts of intellectual capital and property, then examining the varied legal frameworks from which an intellectual capital governance scheme is distilled. The final chapter attempts a synthesis of these definitions and legal approaches to the governance of intellectual capital. The keystones of this synthesis are twofold: first, uniform Canadian legislation; and second, a more focused incorporation of 'property rights' in intellectual capital.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".