Assessing Performance Dimensions in Architecture, Engineer-ing and Construction Organizations
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.
Bibliographic record
Abstract
The collaborative nature of the project environment of the Architecture, Engineering and Construction (AEC) industry necessitates close and prolonged collaboration of diverse organizations in order to execute a project.  For the duration of the project, a certain degree of strategic alignment amongst the participating organizations often becomes necessary for the successful execution of the project.  The impact of such strategic alignments on the organization’s own performance, is often inevitable. While the performance criteria for the project may be clearly defined along with the project’s program and specifications, the performance criteria that each participating organization has set for itself are not always as evident or articulated to others. In this paper, the results of an exploratory field research are presented.  The data analysis revealed that both shared and unique dimensions of performance apply to Architecture, Engineering and Construction organizations. The research findings are significant in that they provide a framework for assessing the degree of compatibility, in terms of shared strategic goals, for firms engaging in projects networks and alliances.
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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 | 0.013 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.010 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it