Investigating Ruptures in Shared Understanding as Recursive Cycles of Mutual Adaptation During Implementation
Bibliographic record
Abstract
Shared understanding between diverse technology stakeholders is a key driver of IT-Business alignment, also underpinning successful adaptive, IS development activities. Lack of shared understanding creates representational gaps, innovation blindness and different technology frames which create barriers to development and implementation of technology. Applying a socio-material perspective to Leonard-Barton’s model of mutual adaptation between technology and organization, as well as research on shared capabilities between IS and business stakeholders, we examine the process by which shared understanding emerges during the design, development and implementation of IT systems. We followed key multi-disciplinary stakeholder groups over a two-year period during the development and implementation of a health information system. We report on events during the project that we call ruptures – highly charged incidents which reveal a lack shared understanding between stakeholders. We argue that ruptures occur during the mutual adaptation of organizational and technological elements necessitated by the implementation process and are precipitated by the constitutive entanglement of social and technological elements. They reveal serious misalignments among stakeholders and in relation to the technology as its material properties become more concrete. We investigate the emergence of ruptures and the mechanisms by which they influence stakeholders, the implementation process and its outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".