Back Campus Fields
Neighbourhood Park, above average overall (score 42, rank ~77th percentile). Strongest: enclosure; weakest: connectivity.
Back Campus Fields scores 41.5 / 100. Strongest dimensions: enclosure / eyes on park and natural comfort. Weakest: amenity diversity (0). Border-vacuum risk is low. This score is a transparent reading of Jane Jacobs-style vitality factors, not a definitive judgment.
Area · 1.28 ha
Weighted across six dimensions · confidence 54%
Scores are not bell-curved. Percentiles and expected scores provide context without changing the underlying model.
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The parks map is loading.Boundary: OpenStreetMap contributors (ODbL).
Explain this score
Where did the 42 come from? Each weighted contribution against a neutral 50 baseline. Green = pushed up; red = pulled down.
Sum of contributions = the headline score. A negative bar means that dimension dragged the park below the city-wide neutral baseline.
Why this park works
Back Campus Fields works because its enclosure score (89) is in the top tier and its edge activation (35) is also top decile (31 mid-rise buildings frame the edge with passive surveillance).
What limits this park
.
Most distinctive characteristic
Most distinctive feature: exceptionally high enclosure (89, top decile).
Jacobs reading
Back Campus Fields sits between an urban social park and an ecological retreat: moderately useful for both, exceptionally suited to neither.
Typology classification
Classified as Neighbourhood Park: 1.3 ha, framed by 31 mid-rise vs 6 towers
Edge Activation
Within 100 m of the park edge: 12 active uses (transit_stop, restaurant, community, cafe) and 4 dead/hostile uses (parking_lot). Active edges keep "eyes on the park" through the day; parking lots, blank institutional walls, rail and highway frontages drain street life.
Source: OSM POIs (amenity/shop) + Toronto Building Footprints + land use
Connectivity
Connectivity blends paths, intersections, transit, entrances, and edge density. This park has 0 mapped paths/walkways and 12 sidewalk segments within 50 m; 4 street intersections within 100 m; 17 transit stops within a 400 m walk; 0 estimated access points across ~455 m of perimeter. low edge density, significant superblock penalty applied. Source coverage: centreline, pedestrian_network, transit_osm.
Source: Toronto Centreline V2 + Pedestrian Network + OSM transit stops
Amenity Diversity
No amenities recorded. Score is 0 until inventory is loaded.
Source: Toronto Parks & Recreation Facilities + OSM amenity tags
Natural Comfort
Natural Comfort requires inputs not yet loaded for this park (Treed Area / Ravine / Waterbodies / Street Trees). Score is held at a neutral 50 with low confidence. Read with caution.
Source: Treed Area / Ravine / Waterbodies / Street Trees
Enclosure / Eyes on Park
49 buildings within 25 m of the park edge (31 mid-rise, 12 low-rise, 6 tower); avg edge height 18.4 m (~6 floors); 10.8 buildings per 100 m of 455 m perimeter (strong frontage density); edges are at a Jacobs-scale walkable mid-rise (3 to 7 floors); 6 towers ≥ 40 m within 25 m of the edge. "Eyes on the park" come strongest from the 31 mid-rise edge buildings.
Source: Toronto 3D Massing (building footprints + heights)
Border Vacuum Risk
Border-vacuum factors within 50 m of the park: parking_lot, parking_lot. Jacobs warned that highways, rail, parking lots and blank institutional edges act as "vacuums" that suppress foot traffic and isolate the park from its neighbourhood.
Source: Toronto Street Centreline (highways) + rail layer + OSM landuse + building footprints
Equity Context
Equity Context requires inputs not yet loaded for this park (Toronto Neighbourhood Profiles). Score is held at a neutral 50 with low confidence. Read with caution.
Source: Toronto Neighbourhood Profiles
Amenities (0)
No amenities recorded for this park.
Nearby active-edge features (39)
- transit stop: Tower Road17 m
- cafe: Diabolos Coffee Bar27 m
- parking lot35 m
- cafe: Acacia Cafe37 m
- transit stop: Tower Road38 m
- parking lot46 m
- community: Hart House Library49 m
- parking lot66 m
- restaurant: The Arbor Room71 m
- cafe: Café Reznikoff72 m
- transit stop: St George Street78 m
- parking lot83 m
- cafe: The Owlery Café92 m
- restaurant: Dining Car94 m
- restaurant: Ideal Catering (Brown Food Truck)99 m
- community: University College Library100 m
- restaurant: Exchange Cafe104 m
- transit stop: St George Street112 m
- rail: Line 1 Yonge-University125 m
- rail: Line 1 Yonge-University126 m
- restaurant: Mama's Best128 m
- parking lot138 m
- cafe: Second Cup143 m
- community: Milt Harris Library147 m
- parking lot151 m
- transit stop: Queen's Part Cres West at Hart House154 m
- highway: Queen's Park Crescent West158 m
- highway: Queen's Park Crescent West159 m
- parking lot160 m
- community: The Buttery160 m
- community: Cheng Yu Tung East Asian Library161 m
- highway: Queen's Park Crescent West167 m
- cafe: Second Cup171 m
- restaurant: Spring Rolls173 m
- restaurant: Ramen Ya174 m
- community: Caven Library175 m
- community: Map & Data Library182 m
- highway: Queen's Park Crescent West188 m
- parking lot: Landmark Garage189 m
Park profile
Five-axis radar across the structural dimensions.
Citywide percentile ranks
Across all Toronto parks in the dataset.
- Overall vitality77th
- Edge activation90th
- Connectivity48th
- Amenity diversity52th
- Natural comfort63th
- Enclosure95th
Most similar parks
Closest in metric space across the five structural dimensions.
- King Georges - Keele ParketteUrban Plaza41
- Old Yonge ParketteUrban Plaza41
- Pitman QuadUrban Plaza45
- Fairchild ParketteUrban Plaza40
- Santa Chiara ParketteUrban Plaza41
Most opposite parks
Furthest in metric space. Useful for recognising what kind of park this isn’t.
- Sir Casimir Gzowski ParkWaterfront Park34
- Budapest ParkWaterfront Park35
- Toronto Islands - Muggs Island ParkRavine / Naturalized Park25
- Rouge ParkWaterfront Park25
- Trca Lands ( 26)Ravine / Naturalized Park27
Human activity signals: not available
No activity signals have landed for this park yet. The model has scored its physical form but it can’t yet say how often it’s programmed, photographed, or walked through. See /data-ethics for what we will and will not collect.
Does this score feel accurate?
Your read of Back Campus Fieldsmatters. We’re testing whether the model lines up with how people actually use the park. Submissions are stored locally; no account needed.
Tell us how this park feels
We measure structure (canopy, edges, connectivity). You measure feeling. Both matter, and disagreement is itself useful civic data.
What would improve this park?
Generated from the weakest measured dimensions: a starting point, not a prescription.
- Activate the edges: encourage cafés, retail or community uses on the streets that face the park; replace blank or parking-lot edges where possible.
- Add or open more entrances and improve sidewalk continuity around the park. More permeability means more spontaneous use.
- Diversify what people can do in the park (playground, washroom, water, shade, performance, sport, garden): even small additions raise this score.
Data sources
- City of Toronto Open Data: Parks (Green Space)Polygon boundaries, official names, types. Boundaries are reconciled against OpenStreetMap (ODbL) for new and updated parks.
- Parks & Recreation FacilitiesInventory of in-park amenities (washrooms, fields, rinks…).
- Toronto Pedestrian NetworkSidewalk segments around and through parks; estimated park entrances.
- Toronto Centreline V2Street segments + intersection nodes near park edges; trails and walkways.
- Toronto 3D MassingBuilding footprints + heights for edge-building counts, frontage density, and tower-in-the-park risk.
- Toronto Treed AreaTree canopy share inside park polygons via stratified-grid sampling.
- Toronto Waterbodies & RiversWater surface inside parks + nearest-water distance for cooling.
- Ravine & Natural Feature ProtectionRavine overlap as a cooling / natural-comfort signal.
- Toronto Street Tree InventoryTree count + density inside park polygons.
- Neighbourhood Profiles(Pending) Equity context proxy.
- OpenStreetMap (Overpass API)Cafés, restaurants, retail, transit stops, parking, highways, rail.