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Record W2509412393

CIO Leadership Characteristics and Styles

2016· article· en· W2509412393 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmericas Conference on Information Systems · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInformation Technology Governance and Strategy
Canadian institutionsQueen's University
Fundersnot available
KeywordsLeadership styleTransactional leadershipShared leadershipPsychologyLeadershipLeadership studiesTransformational leadershipPublic relationsKnowledge managementPolitical scienceComputer scienceSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

Although studies targeting CIO’s leadership characteristics are numerous, studies examining CIOs’ leadership styles are scarce. Today’s CIOs are often members of the firm’s C-level executive team with a wide range of leadership capabilities and characteristics that are not much different from those of the CEOs. What, then, are the characteristics and leadership styles for those CIOs? This literature review study attempts to answer those two questions by examining prior research on these topics. First, we examine prior literature identifying all studied characteristics and then, propose four categories to group them into meaningful sets. Second, we identify what leadership styles are used by researchers. And while the general leadership field has been evolving over the past twenty years shifting its focus and introducing new leadership styles, CIOs' leadership research is still entrapped in the old school of thinking. Consequently, we intend to stimulate new thinking about studying CIOs’ characteristics and styles.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.058
GPT teacher head0.233
Teacher spread0.176 · 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