Challenging Neoclassical Models of Financial Communication: A Canadian Case Study
Bibliographic record
Abstract
This thesis is focused on three dimensions of voluntary disclosure utilized by public corporations to start challenging existing neoclassical assumptions in the literature around financial disclosure.The first dimension is management's understanding of market and investor complexity to effectively reduce information asymmetries.It was found that management can be at an informational disadvantage in trying to understand the investor.Next, is the role of two-way communication in financial disclosure.Twoway communication is seen by management as the most effective form of communication and is used by management to better understand the investor and their needs.Lastly, are the roles of reputation, trust and relationships in financial disclosure.Management views reputation, trust and relationships as key elements of the firm's disclosure policy with financial market participants.In addition to these three dimensions are illustrations of the role that investor relations undertake in helping to facilitate management's understanding of market and investor complexity, two-way communication and building reputation, trust and relationships.A qualitative based case-study approach was used on a unique Canadian situation to provide access to behind the scenes information that may not be readily accessible to an external researcher.The case study and associated results sets the stage for future empirical studies into updating the neoclassical assumptions to better predict the outcome of future events.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.034 | 0.011 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".