Bibliographic record
Abstract
Defining the central identity of the information systems (IS) field is a subject of ongoing concern and debate among IS researchers. Published empirical studies to date have focused on restricted sets of IS-related journal publications spread across relatively short time periods. This paper offers a broader review of the central identity of the IS field, using three dimensions proposed by Albert and Whetten [1985]: central character (i.e., what topics do IS scholars research?); temporal continuity (i.e., to what extent has the identity of the IS field remained static over time?); and distinctiveness (i.e., how unique is research published in IS vs. non-IS research journals?). The first two dimensions are examined using a dataset containing 6,466 journal citations drawn from seven leading IS journals over a 32-year period, and the third is evaluated by comparing results from these seven journals with research published in 15 leading non-IS business journals over the same time period. Results suggest that articles published in leading IS journals do share a strong central character that is distinct from research published in non-IS journals, and yet an identity that has continually shifted over time. This study contributes to the literature by providing an empirically supported review of who we are, how we are different, and some thoughts about where we may be going as a discipline.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.022 | 0.030 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".