Identifying rent pressures [on housing market] in your neighbourhood: a new\nmodel of Irish regional rent indicators. ESRI WP567, June 2017
Bibliographic record
Abstract
Since 2013, researchers in the Economic and Social Research Institute (ESRI)\nhave compiled a hedonic rental index for the Residential Tenancies Board (RTB). The\nindicator estimates a standardised rental index on a national, Dublin and outside of Dublin\nbasis based on the 950,000 rental properties registered with the RTB. The provision in late\n2016 of detailed geographical identifiers has enabled an alternative series of indicators to\nbe estimated. In particular, hedonic rental indicators for 137 local electoral areas (LEAs)\nare now available on a quarterly basis from 2007 quarter 3 to 2016 quarter 4. By providing\na more accurate assessment of regional trends in rental supply and demand, the indicators\nshould enable a more precise implementation of policies in the rental market. They should\nalso serve as a proxy for measuring underlying economic activity in these regions on an\nongoing basis.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".