A negotiator's tool: An Affordable Housing Calculator for voluntary agreements
Bibliographic record
Abstract
Rapid increases in housing costs, stagnant wage growth and limited government funding have created a housing affordability crisis in many cities, in particular in capital cities in Australia. Unlike elsewhere in the world where affordable housing contributions are secured through inclusionary zoning or other planning processes, the Australian context is largely devoid of any mandatory requirements for affordable housing provision in new development. Recent changes to legislation in Victoria have enabled planners to negotiate with developers to secure voluntary affordable housing contributions by offering alternative incentives. However, the lack of financial literacy and understanding of development feasibility and the effects of affordable housing provision on development viability and profit is likely to limit the success of this change. This paper reports on the conceptual framework and development of an Affordable Housing Negotiation Calculator to assist in educating local and state government representatives, community housing providers and developers about affordable housing provision and its effects on development feasibility. It is hoped this tool will enable those decision-makers to better negotiate positive outcomes for an increase in affordable housing while communicating the factors that impact on development feasibility.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".