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Record W4413095381 · doi:10.1016/j.jsis.2025.101923

Generative mechanisms of IT-enabled transformation of a hospital laboratory: A critical realist evaluation

2025· article· en· W4413095381 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of Strategic Information Systems · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsWestern UniversityUniversity of New Brunswick
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGenerative grammarTransformation (genetics)Computer scienceArtificial intelligenceChemistry

Abstract

fetched live from OpenAlex

• 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.

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)0.019
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.908
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.139
GPT teacher head0.401
Teacher spread0.261 · 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