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Record W28894780

Senior Scholars Panel: What Do We Like About the IS Field?

2009· article· en· W28894780 on OpenAlex
John Leslie King, Michael Myers, Suzanne Rivard, Carol Saunders, Ron Weber

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

VenueInternational Conference on Information Systems · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicInformation Systems Theories and Implementation
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsField (mathematics)Cognitive dissonanceSubject (documents)Computer scienceEpistemologyMedia studiesSociologyWorld Wide WebPsychologyPhilosophySocial psychologyMathematics
DOInot available

Abstract

fetched live from OpenAlex

Some of us have been in the information systems field for a long time. What do we like about the field? (Grover et al. 2009). We think the field of information systems is distinctive, perhaps with respect to subject, methods, and a certain way of thinking (Baskerville and Myers 2002; Benbasat and Zmud 2003; Sidorova et al. 2008). Assuming we are not simply drowned in cognitive dissonance, there are important reasons for us to believe in this field and for us to hope that it prospers. We might or might not have a clear and common message about the distinctive nature of the field, but we can at least get some views from some senior scholars who are both smart enough to have jumped ship if they had wanted, and committed enough to see it through. We invite them to present their views, and then we invite the audience to engage in a discussion about the field. Perhaps we might even come up with some clear and common things to say about the field?

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 categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0040.008
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.059
GPT teacher head0.361
Teacher spread0.302 · 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