Do Trees in Halifax Grow on Money?: A Comparison of Urban Tree Canopy Cover and Median Household Income in North End and South End Halifax
Bibliographic record
Abstract
Trees in the city provide numerous ecological, health, and social benefits to urban residents. Studies from large North American cities have confirmed a spatial pattern that higher urban forest tree canopy positively correlates with higher levels of affluence. The just distribution of trees will become increasingly important for urban planners and foresters as there is a national trend towards living in cities. This research report investigates the equity of distribution of urban tree canopy cover in two neighbourhoods on the peninsula of Halifax, Nova Scotia. High spatial resolution land cover data from 2007 and 2006 Statistics Canada census data was used to create maps and tables to answer the research question. The socio-economic indicators of median household income and population density are represented based on census tract dissemination areas from the 2006 Statistics Canada long survey. Preliminary results indicate lower median household income and higher population density in the chosen study area of North End Halifax compared to higher median household income and lower population density in the chosen study area of South End Halifax. Tree canopy cover density is slightly lower in North End Halifax (5.3%) than in South End Halifax (7.6%). These preliminary results coincide with findings of other researchers that higher household income and lower population density at the neighbourhood level may result in increased urban forest canopy. However, further research and more reliant tree canopy cover data is needed to determine the accuracy of these findings.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".