Pathways to Success: Building Support Infrastructures for Internationally Trained Planning Professionals
Bibliographic record
Abstract
<p dir="ltr">Immigration has long been a key contributor to Canadian population growth, economic prosperity, and social vitality and innovation. Economically, the benefit of the ‘brain gain’ — the acquisition of knowledge workers from the rest of the world has given Canada significant advantages by attracting global talents to not only fill the labour shortages, but also contribute to advancing human capital, innovation, and global exchange.</p><p dir="ltr">However, internationally trained professionals often face significant challenges after immigrating to Canada, such as a lack of Canadian work experience, inadequate social and professional networks, and difficulty in obtaining foreign credential recognition for professional licensing and certification. In the planning profession, an accredited planning degree is critical to obtain a full membership with the governing body in order to practice as a Registered Professional Planner in Canada.</p><p dir="ltr">Despite the fact that internationally trained planning professionals (ITPPs) can bring us a wealth of planning knowledge and experience from global planning practices, it has become imperative to provide them with the needed skills and hands-on training to transition and advance their planning careers in the Canadian context. Accredited planning schools can play a pivotal role in creating career-focused curriculum and programs to pave a pathway to success for highly qualified ITPPs. At the School of Urban and Regional Planning, Toronto Metropolitan University, our accredited Master of Planning (MPl) in Urban Development program<a href="https://ontarioplanners.ca/blog/planning-exchange/april-en/pathways-to-success-building-support-infrastructures-for-internationally-trained-planning-professio#_ftn1" target="_blank"><sup>[1]</sup></a> provides an accelerated stream that recognizes international education and experiences and supports ITPPs to obtain much needed training, skills development, and networking opportunities.</p><p dir="ltr">I had the great pleasure working with three ITPPs who recently graduated from our MPl accelerated stream program. I spoke with them about their life stories and professional experiences and aspirations, and found their perspectives shed light on how planning schools can play an important role in developing support infrastructures along with the commitment and investment from employers and accrediting and regulatory professional bodies. The following are the highlights of their backgrounds and responses to four interview questions.</p>
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".