Bibliographic record
Abstract
Introduction This paper introduces the concept of Sustainable Land Rent (SLR), providing a comprehensive, multidimensional exploration anchored in the dynamics of its origin, separability, mobility, valuation, and the imperative for equitable distribution. SLR capitalizes on the economic mobility of land’s value to enhance community welfare and promote environmental sustainability. Advocating for the systematic institutionalization of SLR, the research tackles the complex challenge of distinguishing land value from improvements. Methods Employing traditional Price, Cost, and Income (PCI) methods as practiced in North America, the study addresses the technical challenge of inseparability by estimating and integrating the SLR value within each of these methods. The methodology clarifies the valuation process and establishes an objective framework for resource allocation and negotiation between public and private sectors. Results and discussion Furthermore, our findings highlight SLR’s vital role in advancing public revenue generation and underscore its function as an innovative catalyst for integrating sustainability into economic valuation models and practices in real estate development and urbanization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".