The Scale Illusion: Population Size and the APN Bedrock Score Across Australia's 50 Most Populous LGAs

The Scale Illusion: Population Size and the APN Bedrock Score Across Australia’s 50 Most Populous LGAs

Brisbane holds 1,375,301 people. Knox holds 163,820 — an 8.4-times difference, the largest population gap between any two LGAs in this sample. Their APN Bedrock composite scores are 57.87 and 57.87. Identical, to two decimal places. Across the 50 most populous LGAs, population size explains essentially none of the variation in Bedrock composite: r = 0.077, r² = 0.006. This analysis sets that non-relationship out in full, and rules out population and density as explanations before other factors are considered.

The Non-Relationship

Regressing Bedrock composite on population (Estimated Resident Population, 2025) across the 50 most populous LGAs produces a trend line that is, for practical purposes, flat: across the full range of the sample — from Knox’s 163,820 to Brisbane’s 1,375,301 — the fitted line moves by roughly 5 points. Population accounts for 0.6 per cent of the variance in Bedrock composite. The scatter below shows the shape of that non-relationship directly: LGAs of every size sit at every point on the vertical axis.

Population vs APN Bedrock Composite, All 50 LGAs

20 35 50 65 80 200k 400k 800k 1.4M Population (ERP 2025, log scale) APN Bedrock composite score Brisbane / Knox / Sutherland / Fairfield

Each point is one of the 50 most populous LGAs (population axis log-scaled). Gold points are Brisbane, Knox, Sutherland and Fairfield, referenced in the text. Dashed line is the linear trend (r = 0.077, r² = 0.006).

Same Size, Opposite Outcomes

The clearer test of the non-relationship is not the extremes but the middle. Sutherland (241,327 people) and Fairfield (213,677 people) sit within 13 per cent of each other in population — about as close to “the same size” as any pair in this sample gets. Sutherland posts the highest Bedrock composite score of the 50 LGAs: 73.27. Fairfield posts the lowest: 26.74. A 46.5-point gap, the widest spread anywhere in the data, between two LGAs that are effectively the same size. Whatever separates them, it is not population.

Density Doesn’t Rescue the Story

Population density is a marginally cleaner signal than raw population count, but not by enough to matter. Density correlates with Bedrock composite at r = −0.165 — weak, and in the opposite direction to what a simple “density supports value” thesis would predict. Sydney, the densest LGA in the sample at 9,064 persons per km², posts a middling Bedrock composite of 46.34. Toowoomba, the sparsest at 14.4 persons per km² — roughly 600 times less dense — scores higher, at 53.13. Neither density nor population count offers a usable explanation for Bedrock composite on its own.

Population Density vs APN Bedrock Composite, All 50 LGAs

20 35 50 65 80 10 100 1,000 10,000 Population density, persons per km² (log scale) APN Bedrock composite score Sydney / Toowoomba / Sutherland / Fairfield

Each point is one of the 50 most populous LGAs (density axis log-scaled). Gold points are Sydney, Toowoomba, Sutherland and Fairfield. Dashed line is the linear trend (r = −0.165).

Population Rank vs Bedrock Rank

Ranking all 50 LGAs by population and separately by Bedrock composite makes the scrambling visible at a glance. Brisbane is 1st by population and 8th by Bedrock — a 7-place drop. Knox is 50th by population and tied for 8th by Bedrock — a 42-place rise. Sutherland climbs 21 places, from 22nd by population to 1st by Bedrock; Fairfield falls 22 places, from 28th to 50th. None of the five highest Bedrock scores in the sample belong to a top-10 LGA by population.

Pop. Rank LGA State Population (ERP 2025) Bedrock Composite Bedrock Rank Rank Shift
1 Brisbane Queensland 1,375,301 57.87 8 -7
2 Gold Coast Queensland 691,230 51.13 19 -17
3 Moreton Bay Queensland 532,445 54.22 15 -12
4 Blacktown New South Wales 449,385 45.42 36 -32
5 Casey Victoria 414,929 55.96 10 -5
6 Logan Queensland 403,515 47.38 31 -25
7 Canterbury-Bankstown New South Wales 389,687 35.72 47 -40
8 Sunshine Coast Queensland 381,957 50.97 20 -12
9 Central Coast (NSW) New South Wales 357,816 47.41 30 -21
10 Wyndham Victoria 347,830 47.93 29 -19
11 Greater Geelong Victoria 295,052 50.65 21 -10
12 Parramatta New South Wales 279,014 46.53 34 -22
13 Hume Victoria 278,885 39.66 45 -32
14 Northern Beaches New South Wales 272,656 70.39 2 +12
15 Ipswich Queensland 268,272 43.22 41 -26
16 Liverpool New South Wales 261,231 40.00 44 -28
17 Whittlesea Victoria 259,759 49.02 26 -9
18 Cumberland New South Wales 256,906 27.40 49 -31
19 Stirling Western Australia 254,821 55.45 12 +7
20 Wanneroo Western Australia 246,147 53.99 16 +4
21 Sydney New South Wales 241,797 46.34 35 -14
22 Sutherland New South Wales 241,327 73.27 1 +21
23 Penrith New South Wales 231,701 55.27 14 +9
24 Melton Victoria 231,567 48.08 28 -4
25 Lake Macquarie New South Wales 224,540 49.61 25 0
26 Wollongong New South Wales 224,327 48.17 27 -1
27 The Hills New South Wales 222,675 70.28 3 +24
28 Fairfield New South Wales 213,677 26.74 50 -22
29 Monash Victoria 211,833 47.05 32 -3
30 Townsville Queensland 206,260 46.69 33 -3
31 Brimbank Victoria 198,181 38.84 46 -15
32 Melbourne Victoria 194,481 40.89 43 -11
33 Inner West New South Wales 193,125 55.58 11 +22
34 Campbelltown (NSW) New South Wales 191,285 44.04 39 -5
35 Merri-bek Victoria 189,108 50.03 22 +13
36 Bayside (NSW) New South Wales 187,770 40.91 42 -6
37 Swan Western Australia 187,090 52.79 18 +19
38 Toowoomba Queensland 186,276 53.13 17 +21
39 Whitehorse Victoria 185,256 49.70 24 +15
40 Onkaparinga South Australia 184,827 49.92 23 +17
41 Cairns Queensland 179,334 43.84 40 +1
42 Newcastle New South Wales 178,935 45.21 37 +5
43 Boroondara Victoria 178,601 61.18 6 +37
44 Joondalup Western Australia 176,595 69.11 4 +40
45 Redland Queensland 172,831 44.97 38 +7
46 Mornington Peninsula Victoria 172,217 62.67 5 +41
47 Greater Dandenong Victoria 168,684 33.82 48 -1
48 Kingston (Vic.) Victoria 168,061 58.68 7 +41
49 Georges River New South Wales 163,919 55.28 13 +36
50 Knox Victoria 163,820 57.87 8 +42

What Actually Predicts Bedrock

Ruling population and density out matters because it clears the way for the variables that do carry explanatory weight. A companion analysis of this same sample found IRSAD decile — socio-economic advantage — correlates with Bedrock composite at r = 0.615, and that housing typology (apartment share of dwelling stock) explains a further, independent share of the variance once advantage is controlled for (r = −0.496 against the IRSAD-adjusted residual). Scale was never a serious candidate; this analysis closes that door formally so it does not need reopening.

Methodology Note

Population figures are Estimated Resident Population (ERP) as at 30 June 2025. Population density is persons per square kilometre, calculated from ABS land area figures. APN Bedrock composite is drawn from the APN LGA Intelligence Routine as at 10 July 2026. Correlation coefficients and regression lines (population: Bedrock ≈ 48.703 + 0.00000397 × population; density: Bedrock ≈ 51.225 − 0.000903 × density) are calculated across the 50 most populous LGAs in Australia, compiled through the APN LGA Intelligence Routine — a queue ordered by population, not a random or representative sample. Findings here describe the sample analysed only and should not be read as representative of the full national distribution of Australia’s 547 Local Government Areas.

APN LGA Intelligence
APN LGA Intelligence
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APN LGA Intelligence is Australian Property Network's dedicated Local Government Area research desk, producing data-led LGA profiles drawn from the APN Codex — APN's certified database of ABS, RBA and Census inputs. Coverage spans population trajectory, dwelling stock, socioeconomic indices and building activity, updated as new data is certified.

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