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Record W2805840821 · doi:10.1561/9781680834314

Empirical Research in Information Systems: 2001–2015

2018· book· en· W2805840821 on OpenAlex
Shadi Shuraida, Henri Barki

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

Venuenow publishers, Inc. eBooks · 2018
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsEmpirical researchRelevance (law)Information systemKnowledge managementComputer scienceData scienceEmpirical evidenceManagement information systemsManagement scienceEngineeringEpistemologyPolitical science

Abstract

fetched live from OpenAlex

Empirical Research in Information Systems: 2001-2015 provides a first step in providing empirical evidence and knowledge about the practical relevance of IS research. The monograph first develops a broad yet sufficiently fine-grained framework of IS research by integrating earlier frameworks. It then identifies all empirical IS research published from 2001 to 2015 in four top IS journals (Journal of the Association for Information Systems, Journal of Management Information Systems, Information Systems Research, and MIS Quarterly), and maps onto this framework all the constructs and relationships that were examined by the 1,361 empirical papers published in this 15-year period. Next, based on this mapping and by drawing on criteria proposed by organizational and IS researchers, it provides a preliminary assessment of the relevance of empirical IS research to practice, and discusses the study’s findings and their implications.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0080.011
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.009

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 head0.194
GPT teacher head0.374
Teacher spread0.180 · 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