Citizen involvement in the transportation planning process: What is and what ought to be
Bibliographic record
Abstract
Abstract Public involvement in the transportation planning process is an effort to ensure that citizens have a direct voice in public decision‐making. Through shared goals, such involvement enriches the planning, implementation, operation and management process. Various strategies of involving the public in the planning process have been tried in the past thirty years, but the overall effort has been lumpy and at times disappointing. In the last few years some forms of communicative action have been applied, following its appearance in current literature, but we still have a long way to go. This paper has four main objectives. First, it surveys the citizen involvement effort as it is practiced today and the problems it faces. Second, it describes teleogenic systems that are particularly suited for tackling conflictual problems. Thirdly, it presents the interplay of virtuous and vicious cycles in reinforcing or retarding collective decision making. And lastly, the process of harvesting the potential of citizen groups in collective decision‐making through critical systems thinking is described.
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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 | 0.025 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".