Bibliographic record
Abstract
Abstract Property taxes are common in countries around the world. Until recently, Ireland was an exception as there was no annual tax on residential property. This paper is a review of the Local Property Tax (LPT) system that was introduced in 2013 and had its first property revaluations in 2021. Using the lens of municipal finance and tax assignment, the rationale, history, features and administration of this new residential property tax are outlined. While recognising country-specific circumstances, lessons, opportunities and challenges are explored with a view to future improvements in the design and implementation of the LPT. Lessons from the LPT experience are the importance of tax administration and the role of the central tax collection agency, and, in terms of design, the need for a tailored approach to suit local circumstances. Challenges include the rates/LPT mix and the relative tax burdens on non-residential and residential properties, the long-term sustainability of the LPT arising from design issues, the current low tax rate and future revaluations, and, finally, the need for regular property tax reform because of political and taxpayers’ opposition to a highly visible, unpopular but good local tax.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".