Do Greater Qualifications Imply Higher Bid Costs?
Bibliographic record
Abstract
This study examines the conventional assumption that higher qualifications in A/E consultants or contractors correspond to higher bid costs in the procurement process in construction. By analyzing data from 327 projects across the United States and Canada, encompassing architectural/engineering design and construction projects, including both design-bid-build and alternative delivery methods, the research focused on bid costs and three key qualification-based evaluation criteria: technical proposals, past performance, and interviews. Contrary to common perceptions, the findings, assessed using Spearman's rank correlation and frequency analysis, revealed no significant correlation between higher qualifications and higher bid costs. This finding carries implications for project owners, contractors, and policymakers, suggesting a reconsideration of the emphasis on bid costs alone in the selection process. The study advocates a more detailed approach, considering qualifications alongside bid costs for enhanced project outcomes and collaboration in the construction industry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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; both teacher heads agree on what is shown here.
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".