Age Related Ethical Lapses in Construction Engineering Site Management Decisions
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
Risk chasing can erroneously lead to suboptimal decisions. On construction sites, the pursuit of saving time and money can place construction managers in situations where ethics are involved. In today’s integrated construction sites, younger and more novice construction professionals are increasingly required to make quick decisions on vital matters. Although the impact of age on risk chasing has been thoroughly studied in the behavioral economics literature, a gap was identified in how age affects the propensity of ethical decision making with a key emphasis on construction sites. Based on this knowledge gap, an experiment was developed to compare two groups: (1) one hundred college engineering students with some limited project experience, and (2) forty-eight highly experienced construction leaders. Responses to a set of questions framing a situation common on typical construction sites are compared between the two groups. The findings suggest that the younger respondents are more likely to pursue options that, although they save the project money, are nonetheless unethical. The findings can be used by construction and engineering management professionals to help understand and characterize site decision making behavior, and to support the development of training tools to mitigate the costs associated with unethical and suboptimal decisions.
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 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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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