Novel Approach to Overcoming Discontinuity in Knowledge: Application in Value-Adding Frameworks in Construction Industry
Bibliographic record
Abstract
Knowledge discontinuity can be a significant obstacle to knowledge growth and accumulation, resulting primarily from the excessive tailoring of borrowed concepts, theories, and approaches. Research in the construction industry is prone to knowledge discontinuity because often after adopting a concept originally developed in another field of study, the link to the original trunk is gradually severed, thus inhibiting research progress. In fact, knowledge discontinuity slows advancement in the construction industry because it is an obstacle to the realization of the benefits achieved in other disciplines by means of the concept, theory, or approach. The research presented in this paper proposes a novel approach to overcoming the discontinuity in knowledge in construction-related research. It uses value-adding practice in the construction industry as a case study, establishing a common understanding of the predominant value-adding frameworks used in the construction industry and providing a measure for the similarity between the selected value-adding frameworks along with the shortcomings of the value-adding practice that need to be addressed. The paper concludes with defining the requirements for a unified framework for value adding in the construction industry.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".