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Record W2180775198 · doi:10.19030/rbis.v13i4.4308

Information Technology: Market Success To Succession

2009· article· en· W2180775198 on OpenAlexaff
Christopher S. Wright, Isaam Dawood

Bibliographic record

VenueReview of Business Information Systems (RBIS) · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsLakehead University
Fundersnot available
KeywordsEcological successionSuccession planningBusinessEcologyBiologyFinance

Abstract

fetched live from OpenAlex

Since commercial computers were first introduced in the early 1950s, their role, power, and importance has so expanded that the current period is often called The Information Age. Over the past decade, policy makers and the public have become progressively more concerned as success in information markets has lead to a concentration of market power that allows a few firms to dominate what is increasingly seen as a commodity essential to modern life. This paper argues that, in modern information markets, success allows domination but also creates the conditions that lead to succession – the giants of one micro-age tend to become commodity suppliers to the movers and shakers of the next micro-age. This study separates the first 50 years of The Information Age into the Hardware and the Software Micro-ages. It is suggested that the user-training focus, of the now dawning Wetware Micro-age, will profoundly affect information markets and practises.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.007
Science and technology studies0.0000.000
Scholarly communication0.0000.019
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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; a candidate call from one teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2009
Admission routes1
Has abstractyes

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