MétaCan
Menu
Back to cohort
Record W2053501423 · doi:10.1108/02635570110394635

A socio‐technical framework for quality assessment of computer information systems

2001· article· en· W2053501423 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

VenueIndustrial Management & Data Systems · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicInformation Systems Theories and Implementation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSociotechnical systemSuiteContext (archaeology)StakeholderQuality (philosophy)Knowledge managementField (mathematics)Information systemComputer scienceQuality management systemKey (lock)Process managementEngineering managementEngineeringQuality managementManagement systemOperations managementManagementComputer securityPolitical science

Abstract

fetched live from OpenAlex

The emergence of total quality management and the ISO 9000 suite of standards has allowed a re‐think of how (and why) the post‐implementation evaluation of computer systems is to be carried out. Traditional performance measurement, modeling and analysis techniques – while not discredited – have been tempered with a more holistic ideology. This article recommends a socio‐technical approach to determining the quality of a computer information system. In this context, two postulates have been proposed and tested by field survey of expert systems in the insurance industry in North America. Postulate one focuses on a multidimensional concept of IS quality comprising the characteristics of task, technology, people and organization. Postulate two deals with differences in assessments of these characteristics according to stakeholder groups: managers, developers, and users. Summarizes the key findings of these postulates in the context of the TQM and ISO 9000 philosophies.

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)0.008
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
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 head0.250
GPT teacher head0.456
Teacher spread0.206 · 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