Advancing the Fifth Hand explanation of project cost misperformance
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
Cost misperformance in projects from contract award, expressed through cost growth and margin erosion, is a problem that confronts construction organisations worldwide. While several conceptual theories have attempted to explain cost misperformance, they often fail to account for how and why it arises in specific project contexts. The Fifth Hand has emerged as a pragmatist explanatory construct, but it has yet to be empirically tested. This paper extends its application by drawing on Evidential Pluralism, the idea that no single form of evidence suffices for causal inference, and epistemic causality, which focuses on how causal knowledge is justified. Integrating these perspectives strengthens the Fifth Hand’s foundations for context-sensitive, evidence-informed explanations. Using an explanatory case study, we address two research questions: (1) What associations and causal mechanisms contribute to cost misperformance in construction projects? And (2) How can a pluralistic, evidence-based analysis advance the Fifth Hand’s explanatory power? Statistical analysis for a sample of 67 projects, totalling $3.22 billion in value, delivered by a construction organisation, revealed associations between cost growth and margin gap (negative) and project size (positive), with unapproved subcontract variations predicting margin erosion. Qualitative analysis identified organisation-wide mechanisms, temporal discounting, disengagement from systems, and overconfidence, as well as project-specific mechanisms such as external design-related ambiguity and internal planning failures. Theoretically, this paper extends the Fifth Hand by integrating pluralistic approaches to evidence and causal reasoning. Practically, it offers construction organisations insights into behavioural and systemic vulnerabilities that contribute to cost misperformance.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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