Bridging the Gap between Academic and Practice Quantity Surveying in Nigerian Construction Industry
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
In the construction industry worldwide there is a recognizable gap between academics construction knowledge and its application, and construction knowledge and application as seen in field of practice. In Nigeria, the Quantity surveying profession like other professions in the industry, suffers this same fate. It is based on this that this paper identified the possible factors causing gap between the two divisions. A survey approach was adopted, and questionnaire was used to gather data from construction professionals both in practice and in academics, Ondo State. Data gathered were analyzed using percentage, mean item score and Mann-Whitney U Test. Findings revealed that the major factors contributing to gap are majorly more theoretical knowledge than practical, inadequacy in educational curriculum, slow adoption of innovations and inadequate trained personnel. The two categories of respondents( practicing respondents and those in academics) believes that the most important factor that can help and in bridge the gap between QS in Academics and QS in practice is frequent organizing workshop, lectures and seminars which has been identified by past literature. Openness to new innovations, equilibrium of theoretical and practical knowledge, are the closely following factors. This study contributes to body of knowledge on this subject of discuss.
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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 | 0.001 | 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 | 0.001 | 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