Conceptualizing Information Systems Development as an Organizational Routine
Bibliographic record
Abstract
Research acknowledges that information systems development (ISD) teams experiment with, overlook, or adapt the methods that they purportedly use. Given this, one stream of research adopts a perspective focused on prescriptions based on the idea of a method. Another stream of research adopts a perspective anchored in the view that human agency plays a critical role in the unfolding of ISD projects. We suggest that our understanding of ISD can be enriched by mobilizing both perspectives. Specifically, we propose a conceptualization of ISD as an organizational routine based on the ontology developed by Feldman and Pentland. We build on the elements of this ontology- (1) the idea of a routine (the ostensive aspect) and (2) its enactment (the performative aspect) as the two mutually constitutive aspects of organizational routines; and (3) the role of artifacts as mediators of the relationship between actors and the ostensive and performative aspects of organizational routines - to develop theoretical arguments explaining the benefits of applying this ontology to the ISD phenomenon. Extending the contextual boundaries of Feldman and Pentland's ontology, we propose research avenues that have the potential to contribute to our understanding of this core phenomenon of the IS 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.003 | 0.044 |
| Scholarly communication | 0.014 | 0.020 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".