Bibliographic record
Abstract
Environmental Impact Assessment (EIA) provides for the assessment of the likely significant effects of a proposed development in the environment. Due to the ambiguous nature of the legislation on EIA, there are widely differing views as to whether the impact of a proposed development o surrounding property values should be considered as part of the EIA process. The primary objective of this thesis was to establish if property values should be considered within the Irish EIA process. In this regard, the most relevant provisions of the EC Directive 97/11/EC and the corresponding Irish legislation (Part X of the Planning and Development Act 2000 and Part 10 of the Planning and Development Regulations 2001) were reviewed and it was established how these legislative provisions were being interpreted in practice. This was achieved by means of interviews with key personnel in the Irish EIA process and through a review of all of the Environmental Impact Statements submitted to ‘competent authorities ‘in Ireland over a ten year period. The thesis concludes that ‘impacts on property values’ are economic impacts upon “human beings” and “material assets” i.e. land and/or property, and as such, they should be considered in the Irish EIA process., but only in instances where the potential impact of the proposed development on property values is likely to be significant. The secondary objective of the thesis was to establish if it was possible to devise a suitable quantitative methodology for property value assessment for application in the Irish EIA process. Three quantitative methods were identified that have been used for property value assessment in countries such as the UK, the USA, Canada and Australia. The methods were the hedonic pricing method, the ‘before and after’ study method and the benefits/costs transfer method. These methods have been applied to a limited extent in EIA world-wide. The study, explores, through the use of case studies, the practical application of the three quantitative methods to property value assessment in the Irish EIA process. However, the thesis concludes that there are a number of inherent problems which need to be overcome in formulating and testing a quantitative approach and methodology for the assessment of the potential impact of a proposed development on property values. The main problem is the lack of public access to accurate and detailed information on both property transactions and environmental considerations.
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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 | 0.073 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".