The Integration of Green Infrastructure and Equity within Urban Planning: An Academic and Applicative Exploration
Bibliographic record
Abstract
This thesis examines the integration of green infrastructure and equity within academia and in practical applications such as comprehensive city plans. With climate change worsening and affecting urban areas with extreme weather events, many municipal governments are developing and implementing higher numbers of green infrastructure projects. However, cities need ensure that all residents are benefiting from green infrastructure otherwise those already at a risk of negative impacts from climate change may continue to be affected, or have those impacts exacerbated. \n \nThe goal of the first manuscript was to conduct a systematic literature review to explore 47 contemporary articles with the goal of identifying an overlap between equity and green infrastructure integration in urban planning. It is necessary to understand the integration, or lack thereof, of equity and green infrastructure in urban planning literature so that future research can fill in those missing considerations and build upon past work. Present research does indicate that green infrastructure and equity need to be considered in conjunction with one another so that the negative consequences of unconscious ignorance in planning is avoided. The second manuscript applies this research with the creation of a framework to evaluate Resilience Strategies – part of the “100 Resilient Cities” program by the Rockefeller Foundation, and comprehensive city plans, such as climate change adaptation plans. Eight plans were evaluated for four Canadian Cities: Toronto, Vancouver, Calgary, and Montréal. \n \nMy research concludes that research in green infrastructure and equity is growing as most papers were published within the last 5 years (2015 – 2021), but further acknowledgement of various types of equity and intersectionality need to be considered in green infrastructure research. In addition, resilience strategies and comprehensive city plans were lacking in equity considerations in green infrastructure implementation. The scores for the eight plans in four Canadian cities assessed vary from 5 out of 25 to 15.5 out of 25. A standardized framework to help apply an equity lens for green infrastructure implementation can help ensure that there will be consistent necessary considerations for green infrastructure and equity in city planning. Comprehensive city plans and resilience strategies need to have equity considerations to ensure that the benefits of green infrastructure can reach all populations as needed, and to prevent the exacerbation of socioeconomic inequality. Altogether, improving the integration of equity and green infrastructure in cities can support climate change mitigation and adaptation for all residents and help to build a more sustainable future.
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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".