Designing and implementing a local residential property tax from scratch: lessons from the Republic of Ireland
Bibliographic record
Abstract
Assigning recurrent taxes on immovable property to cities, municipalities, and rural districts is a common practice around the world. The Republic of Ireland is no different, with its annual taxes on real property assigned to local government. Following the 2008 financial crisis and the austerity era that ensued, Ireland’s property taxes underwent major reform, most notably the design and implementation of a new residential property tax 35 years after abolition of the previous system of ‘rates’ on residential properties. In this paper the new or different features of Ireland’s residential property tax are outlined, including the use of self-assessment and valuation bands, innovative payment methods and also the multiple compliance mechanisms for taxpayers. While recognising the importance of country-specific and local circumstances in property tax design, the paper concludes that elements of Ireland’s new residential property tax have potential lessons for other jurisdictions contemplating similar tax reform. These relate to the key tax principles of simplicity and public acceptability, and on specific design features of assessment and valuation, and collection and compliance.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".