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Record W1969127334 · doi:10.1177/154193120004400418

A Work Domain Analysis for Network Management

2000· article· en· W1969127334 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

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2000
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceHierarchyAbstractionDomain (mathematical analysis)Interface (matter)Work (physics)Task (project management)Distributed computingSoftware engineeringHuman–computer interactionSystems engineeringEngineeringOperating system

Abstract

fetched live from OpenAlex

Computer networks are pervasive and critical to the operation of today's businesses. While most of us take computer networks for granted, network managers who must configure, operate, and fix faults in computer networks face a daunting task that becomes more complex everyday. Ecological interface design has been shown to be a promising approach for complex systems such as power plants or petrochemical systems. Computer networks are a very different work domain characterized by rapid technological change, extreme decentralization, and the existence of “soft” components. This paper presents the first work domain analysis of this new domain creating an abstraction hierarchy for general signal transfer systems and general computing networks. It shows how the abstraction hierarchy can be applied to this new domain and presents the initial work on an ecological interface design for network management.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.504
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.244
Teacher spread0.224 · 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