Why Did the “Missing Middle” Miss the Train? An Actors-In-Systems Exploration of Barriers to Intensified Family Housing in Waterloo Region, Canada
Bibliographic record
Abstract
(1) Background: Missing Middle (MM) housing may be critical to address decreasing housing affordability and to achieve critical density in transit-oriented neighborhoods; however, its production is in decline. We report on a case study of housing development around a new light-rail transit line in the Region of Waterloo, Canada, investigating the puzzle of how a residential building boom coincided with decreasing housing affordability. (2) Methods: Following participatory co-creation and communication of background research characterizing housing demand with stakeholder partners, we created a data narrative arguing that MM housing was desired by residents and profitable for developers and then used it to guide semi-structured interviews with planners and real estate industry stakeholders. Based on these interviews, we developed a qualitative system map and causal loop diagrams that demonstrate interactions between key actors (residents, brokers, planners, developers, and investors) as mediated by boundedly rational real estate demand expectations. (3) Results: Our interviews identify multi-faceted barriers, beyond demand perception, to MM housing development. Systems analysis illustrates how high-density, small-unit high-rise development can become locked in, concurrently locking out MM housing. (4) Conclusions: Our research identifies barriers to MM housing supply by articulating the systemic feedbacks between the planning and land/housing market realms and reveals key leverage points, empowering planners to develop policies that catalyze hoped-for housing market supply responses to increase housing affordability. Based on these findings, we suggest targeted interventions: multi-unit base residential zoning, MM site plan typologies, non-profit and co-op financing, unit-mix requirements, pre-build MM condo purchase by municipalities or non-profits, and MM demonstration projects.
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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 | 0.001 | 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".