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Record W2003472190 · doi:10.1108/09513571211263211

Metaphor in Nortel's letters to shareholders 1997‐2006

2012· article· en· W2003472190 on OpenAlexaff
Merridee Bujaki, Bruce J. McConomy

Bibliographic record

VenueAccounting Auditing & Accountability Journal · 2012
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsMetaphorCorporationShareholderOriginalityMeaning (existential)Value (mathematics)BusinessPublic relationsPsychologyAccountingSociologyPolitical scienceQualitative researchLinguisticsSocial scienceComputer scienceFinanceCorporate governancePhilosophy

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.029
GPT teacher head0.309
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations26
Published2012
Admission routes1
Has abstractyes

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