The Politics of Urban Transport in New Zealand
Bibliographic record
Abstract
Transport planning literature documents high density urban development, low car usage, large numbers of non-motorized and public transport trips, as indicators of a high quality sustainable urban transport system. Wellington, the capital of New Zealand, relatively fulfills the requirements of these indicators. However, Wellington´s transport planning over the last fifty years has been focused on private vehicles and building wide and better roads, motorways and tunnels. Main stream politicians as well as transport professionals present these projects as urban transport achievements. Unfortunately, the massive road infrastructure projects absorb all transport funding in the city and shift attention away from the core issues of integrating land use and transport planning. In fact, all these projects were based on faulty assumptions that traffic congestion would be relieved and Wellington´s environmental quality would be improved. The result is increasing congestion and unhealthy air and noise pollution in Wellington. If Wellington wants to raise its status as a liveable city, it needs to follow the lead of cities such as Vancouver in Canada and Zurich that outperform Wellington in the liveablity city rankings. These cities assessed their performance of liveablity in the light of ‘balanced transport system planning´ approach proposed by Professor Vukan Vuchic (1999). The purpose of this paper is to apply Vuchic´s transport planning approach to carry out a document analysis reviewing the major transport and planning policies in the Wellington Region, identifying the current opportunities and constraints to achieving integration of land use and transport planning. In addition, constraints which are caused by the institutional characteristics of the government agencies will also be considered. This research finds that for Wellington to achieve success in the light of a balanced transport system planning approach; improved investment in software at Vuchic´s Level 1, 2 and 3. The investment in software should include improvement of coordination among different organisations, strengthening of public transport organisations and network planning for public transport development. Only small fixes improving the capability in transport planning institutions can help to integrate transport planning with land use in Wellington, which international evidence suggests, is more productive than single focus strategies on transport projects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".