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Record W123188105 · doi:10.3233/hsm-2009-0693

Architectural Leadership: Building a value enhancing infrastructure

2009· article· en· W123188105 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

VenueHuman Systems Management · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsYork University
Fundersnot available
KeywordsCompetitive advantageValue (mathematics)BusinessNature versus nurtureCost leadershipStrategic leadershipKnowledge managementPublic relationsProcess managementManagementMarketingStrategic planningComputer scienceSociologyEconomicsPolitical science

Abstract

fetched live from OpenAlex

Architectural Leadership is a new approach to leadership intended to assist CEOs in overcoming obstacles, implementing strategy, achieving performance improvement and enhancing value. The Architect Leader structures value-drivers through unique core organizational Methods, which embody improved capabilities, serve strategy and widen the strategic horizon. The Architect Leader assimilates the Methods in the organization and ensures application of lessons learned and adjustment of the Methods to the varying circumstances. Architect Leaders nurture leadership at all organizational levels, encourage initiatives and harness all employees, not just the executive team, to fulfill the organization's goals. The Architectural Leadership approach is practical, accessible and does not require charisma. It is based on extensive experience and has successfully been applied in many business and governmental organizations and in various industries as a means of creating competitive advantage and increasing value.

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 categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.807
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.027
GPT teacher head0.235
Teacher spread0.208 · 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