Bibliographic record
Abstract
City and regional planning is a vibrant, young, rapidly expanding profession. It is both an art and a science. Planners may be called city planners, regional planners, or rural planners if their practice is mainly restricted to one type of jurisdiction. City and regional planners work at the national, state, regional, city, county, and community level. Some planners work in private architectural, engineering, planning, and urban design consulting firms, for nonprofit agencies, or in the public sector. U.S. city and regional planners are educated as generalists with a specialty. Planning specialties include transportation, environmental, housing, economic, and community development planning and other areas. The Planning Accreditation Board (PAB) accredits city and regional planning degree programs in the United States. The PAB may also accredit Canadian planning programs. However as of Spring, 2022 the University of British Columbia was the only PAB-accredited planning program in Canada. Canada’s Professional Standards Board (PSB)—not the CIP—administers its own certification process of professional planners on behalf of the Provincial and Territorial Institutes and Associations (PTIAs), except in Québec. However, regulatory responsibilities are held by the PTIAs. In Quebec L’Ordre des urbanistes du Québec (OUQ) accredits and administer three planning schools in Québec. City and regional planning professionals do not have an accreditation or licensing system comparable to law, medicine, and engineering. The American Planning Association (APA) is the professional association of city and regional planners practicing in the United States. It primarily serves U.S. city and regional planners, but has dozens of members from other countries. The APA’s American Institute of Certified Planners (AICP) certifies planners, but only New Jersey require planners to be AICP-certified to practice city and regional planning.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.026 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".