Generative mechanisms of IT-enabled transformation of a hospital laboratory: A critical realist evaluation
Bibliographic record
Abstract
• In transformation, social and technical components interact and evolve to drive joint optimization. • Generative mechanisms unpack how social and technical components interact and co-evolve in IT-enabled transformation.. • IT-enabled transformation is driven by inertia disruption, cognitive frame alignment, auto-validation, and affordance actualization. • Organizations must create appropriate conditions for generative mechanisms to manifest. • Dependencies exist among generative mechanisms. Research efforts in the domain of IT-enabled Organizational Transformation (ITOT) have predominantly focused on identifying the determinants contributing to success in ITOT and the significance of their existing theories. However, the socio-technical dynamics driving the transformation process remain largely understudied. To understand and adequately investigate how the organization transformation process emerges and evolves over time, we need to examine how the social and technical components interact through human agents and under different contextual conditions to enable successful IT-enabled transformations. Considering these social and technical components and their interactions as constitutive of generative mechanisms — that is, the causal mechanisms posited by critical realism — we conducted an in-depth case study of a hospital laboratory’s IT-enabled transformation efforts. Through a critical realist lens, we provide a rich description of key generative mechanisms that contributed towards this laboratory’s successful transformation. Among them, our analysis identifies four noteworthy generative mechanisms which manifested over time to progress the transformation process: (1) inertia disruption; (2) cognitive frame alignment; (3) auto-validation; and (4) affordance actualization. At this laboratory, each and every generative mechanism identified demonstrates how interactions among social and technical components — mediated by the laboratory employees — lead to evolving structural configurations over time, facilitating overall transformation. Our goal is to offer a theoretical explanation by way of generative mechanisms to explain not only how but why the laboratory transformation vision emerged and evolved. Our research advances a causal understanding of the socio-technical process of IT-enabled organizational transformation and offers a rigorous example of applying critical realism and generative mechanisms perspective to study complex IT phenomena.
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.
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 | 0.044 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".