Metaphor in Nortel's letters to shareholders 1997‐2006
Bibliographic record
Abstract
Purpose This paper seeks to analyze the use of metaphor in the 1997‐2006 letters to shareholders (LTS) of Nortel Networks Corporation (Nortel). It aims to assess the prevalence of metaphor and changes in the use of metaphor as turnover in corporate leadership took place and as Nortel's financial fortunes changed. Design/methodology/approach Metaphors in the LTS are part of a corporation's voluntary disclosures, which in turn may be used for impression management purposes. The paper uses discourse analysis, in particular quantitative and qualitative content analysis, of the LTS to identify key metaphors and to evaluate changes in the prevalence of these metaphors across corporate leaders and during phases of growth and decline. Findings Several key metaphors are identified in Nortel's letters to shareholders, including science, journey, vision, construction and theatre. Evidence is also found that demonstrates changes in the prevalence of metaphors across various chief executive officers, and changes in the meaning of metaphors in periods of growth and decline. Originality/value The contribution of the paper is to highlight the use of metaphor in the voluntary disclosures (i.e. letters to shareholders) of a major North American corporation during a turbulent decade. The preferences of four very different CEOs are reflected in their choice of metaphor, supporting arguments that metaphor is used in voluntary disclosures as a means of impression management, particularly in relation to trends in corporate financial performance.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".