feat: Implement Phase 4 dbt model restructuring

Create neighbourhood-centric dbt transformation layer:

Staging (5 models):
- stg_toronto__neighbourhoods - Neighbourhood dimension
- stg_toronto__census - Census demographics
- stg_toronto__crime - Crime statistics
- stg_toronto__amenities - Amenity counts
- stg_cmhc__zone_crosswalk - Zone-to-neighbourhood weights

Intermediate (5 models):
- int_neighbourhood__demographics - Combined census with quintiles
- int_neighbourhood__housing - Housing + affordability indicators
- int_neighbourhood__crime_summary - Aggregated crime with YoY
- int_neighbourhood__amenity_scores - Per-capita amenity metrics
- int_rentals__neighbourhood_allocated - CMHC via area weights

Marts (5 models):
- mart_neighbourhood_overview - Composite livability score
- mart_neighbourhood_housing - Affordability index
- mart_neighbourhood_safety - Crime rates per 100K
- mart_neighbourhood_demographics - Income/age indices
- mart_neighbourhood_amenities - Amenity index

Closes #60, #61, #62, #63

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

dbt/models/marts/mart_neighbourhood_amenities.sql

@@ -0,0 +1,89 @@
+-- Mart: Neighbourhood Amenities Analysis
+-- Dashboard Tab: Amenities
+-- Grain: One row per neighbourhood per year
+
+with amenities as (
+    select * from {{ ref('int_neighbourhood__amenity_scores') }}
+),
+
+-- City-wide averages for comparison
+city_avg as (
+    select
+        year,
+        avg(parks_per_1000) as city_avg_parks,
+        avg(schools_per_1000) as city_avg_schools,
+        avg(transit_per_1000) as city_avg_transit,
+        avg(total_amenities_per_1000) as city_avg_total_amenities
+    from amenities
+    group by year
+),
+
+final as (
+    select
+        a.neighbourhood_id,
+        a.neighbourhood_name,
+        a.geometry,
+        a.population,
+        a.land_area_sqkm,
+        a.year,
+
+        -- Raw counts
+        a.parks_count,
+        a.schools_count,
+        a.transit_count,
+        a.libraries_count,
+        a.community_centres_count,
+        a.recreation_count,
+        a.total_amenities,
+
+        -- Per 1000 population
+        a.parks_per_1000,
+        a.schools_per_1000,
+        a.transit_per_1000,
+        a.total_amenities_per_1000,
+
+        -- Per square km
+        a.amenities_per_sqkm,
+
+        -- City averages
+        round(ca.city_avg_parks::numeric, 3) as city_avg_parks_per_1000,
+        round(ca.city_avg_schools::numeric, 3) as city_avg_schools_per_1000,
+        round(ca.city_avg_transit::numeric, 3) as city_avg_transit_per_1000,
+
+        -- Amenity index (100 = city average)
+        case
+            when ca.city_avg_total_amenities > 0
+            then round(a.total_amenities_per_1000 / ca.city_avg_total_amenities * 100, 1)
+            else null
+        end as amenity_index,
+
+        -- Category indices
+        case
+            when ca.city_avg_parks > 0
+            then round(a.parks_per_1000 / ca.city_avg_parks * 100, 1)
+            else null
+        end as parks_index,
+
+        case
+            when ca.city_avg_schools > 0
+            then round(a.schools_per_1000 / ca.city_avg_schools * 100, 1)
+            else null
+        end as schools_index,
+
+        case
+            when ca.city_avg_transit > 0
+            then round(a.transit_per_1000 / ca.city_avg_transit * 100, 1)
+            else null
+        end as transit_index,
+
+        -- Amenity tier (1 = best, 5 = lowest)
+        ntile(5) over (
+            partition by a.year
+            order by a.total_amenities_per_1000 desc
+        ) as amenity_tier
+
+    from amenities a
+    left join city_avg ca on a.year = ca.year
+)
+
+select * from final