The Urban and Regional Studies Multidisciplinary Major at the University of Lethbridge: A History 1970-1989
Bibliographic record
Abstract
The Urban and Regional Studies Multidisciplinary major was developed within the Department of Geography, University of Lethbridge, and was coordinated by Professor George Zieber from 1971 until 1989, when he retired.Thereafter, it was coordinated by others in the department.It is the longest-standing multidisciplinary major at the University, a highly successful program, and has been a model for the development of similar programs.The major has played a very important role in training students to become urban and regional planners, many of whom are practicing as such within Alberta.Graduates also have been able to fill positions in a variety of other urban and regional related fields, as well as to go on to graduate studies in areas such as planning, architecture and law.Some of these students received prestigious graduate scholarships and also recognition for outstanding academic work.The Urban and Regional Studies Multidisciplinary major was somewhat unique in that few universities in Canada offered a planning or planning-related program at the undergraduate level.Moreover, it provided majors not only with a Canadian and international perspective on the nature and problems of planning cities and regions but also with a specifically Western Canadian one.The idea of the major was brought to the Department by Professor Elbert Miller from Western Washington University, when George Zieber recruited him in 1968.In 1970, while Zieber was on leave, Miller selected courses as a core for the major from four departments: Geography, Economics, Political Science, and Sociology.A fifth list included primarily individual courses from other departments and were ones chosen to provide more breadth to the major.In 1971, George Zieber was asked to take over the major because of his specialization in Urban Geography and in Planning in his doctorate degree.Throughout the span of 19 years that he served as Coordinator, he carried sole responsibility for its administration, direction, and development.Student interest in the program increased quickly.During some of those years, the number of majors enrolled was in the same range as those enrolled in large departments such as Chemistry, Economics, and Sociology.Zieber believes that one of the main reasons for the success of the program was the commitment to give thorough and consistent counseling and guidance to the majors, as well as to work closely with them during their individual assignments and group projects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.052 | 0.007 |
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".