MétaCan
Menu
Back to cohort

Toward an Autopoietic Approach for Information Systems Development

2001· book-chapter· en· W1538418903 on OpenAlexaff
El‐Sayed Abou‐Zeid

Bibliographic record

VenueIGI Global eBooks · 2001
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicInformation Technology Governance and Strategy
Canadian institutionsConcordia University
Fundersnot available
KeywordsAutopoiesisInformation systemComputer scienceDomain (mathematical analysis)Strengths and weaknessesMainstreamScope (computer science)Independence (probability theory)Component (thermodynamics)Knowledge managementManagement scienceData scienceEngineeringArtificial intelligenceEpistemologyMathematicsPolitical science

Abstract

fetched live from OpenAlex

Several weaknesses of information systems development methodologies have been identified and studied in the recent years. These weaknesses can be viewed from different perspectives such as: • The characteristics of the outcomes, i.e., information systems: The current methodologies are producing systems with rigid and inflexible that are difficult to maintain and to evolve (e.g., Loucopoulos, 1991). • The degree of the domain-independence: There is a gap between the way system development methodologies in the mainstream of scientific and technical literature and the way they are carried out in real life situations. This is mainly due to the domain-independence of most of these methodologies (Bansler & Bolker, 1993, Vessy & Glass, 1998). • The conceptual and philosophical bases: The dominance of the functionalistic view in the most of current methodologies (Hirschheim, Klein & Lyytinen, 1995, Iivari, 1991, Iivari, Hirschheim & Klein, 1998). In addition, most of information systems development methodologies under-utilize the richness of concepts and insights provided by new and emerging theories such as autopoiesis, self-organization, and fuzzy logic. Moreover, they do not accommodate the new emerging information systems and technologies such as component and framework technologies, web-enabled information systems and ERP.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.934
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.216
Teacher spread0.189 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueIGI Global eBooksSame topicInformation Technology Governance and StrategyFrench-language works237,207