Corporate communication as a governance mechanism: A content analysis of corporate public disclosures
Bibliographic record
Abstract
Corporate communication efforts have mainly been viewed as a by-product of governmental regulations and board of directors’ oversight. In this paper, we examine the role of corporate communication as a stand-alone governance mechanism. We introduce a new business-related dictionary and conduct automated textual analysis of over 150,000 electronic documents filed by a sample of firms listed on the S&P/TSX Composite Index from 1999 to the end of 2014. Our findings demonstrate the governing role of corporate communication by documenting the adverse market effects of deviations from the expected level of communication. Moreover, as a governance mechanism, corporate communication shows substitution/complementary relationships with other established governance mechanisms. In addition, we find a non-linear relationship between a firm’s communication efforts and its value and risk levels. Results are robust after controlling for major corporate events (M&A, spin-offs, financial distress and bankruptcy, and significant lawsuits). These findings contribute to corporate governance literature and the understanding of agency theory predictions of communications and disclosures’ economic effects
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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 | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".