Bibliographic record
Abstract
Interorganizational systems (IOS) are information and communication technology-based systems that transcend organizational boundaries. However, their use does not always lead to successful interorganizational collaboration, particularly in settings where significant changes in business processes are needed. The architecture, engineering and construction (AEC) industry offers such a setting, in particular as its stakeholders are encouraged to use of a novel type of interorganizational system known as building information modeling (Building Information Modelling), which can only be successfully used if parties collaborate. This research seeks to uncover what leads to interorganizational collaboration in this particular context. Drawing on rich data from interviews with BIM users involved in interorganizational projects, the authors propose a conceptual model of how interorganizational collaboration unfolds. The authors highlight the central role played by interorganizational infrastructure, collective identity, and IT affordances, on interorganizational collaboration.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".