Spatial inequalities: WACE Year 12 Geography
“Analyse the spatial inequalities produced by global networks and how they are measured”
Spatial inequality is the uneven distribution of wealth, opportunity and wellbeing across space; global networks tend to concentrate investment, jobs and profit in core regions while leaving peripheries behind, producing gaps both between countries and within them, which geographers measure using indicators such as GNI per capita, the Gini coefficient and the Human Development Index.
What this dot point is asking
SCSA wants you to explain how globalisation produces uneven outcomes, identify the patterns of inequality between and within places, describe how inequality is measured, and evaluate why some places benefit more than others. A strong answer distinguishes inequality at different scales and uses named measures and examples.
What spatial inequality means
Spatial inequality is the unequal distribution of resources, income, services and life chances across geographic areas. Globalisation does not spread benefits evenly. Investment, high-value jobs and infrastructure cluster in well-connected nodes, while poorly connected places are bypassed. The result is winners and losers at every scale.
It is important to analyse inequality at multiple scales:
- Between countries: the gap between high-income and low-income economies.
- Within countries: gaps between regions, such as booming capital cities versus declining rural or rust-belt areas.
- Within cities: wealthy and disadvantaged neighbourhoods side by side.
How global networks create inequality
Several mechanisms concentrate advantage:
- Cumulative causation. Once a place attracts investment, it gains infrastructure, skills and further investment, pulling ahead of others, while peripheries lose people and capital to the core.
- Value capture. As production and value chains show, design and branding capture most profit, so countries that only supply raw materials or assembly earn little.
- Connectivity. Places linked into global networks (major ports, financial centres, tech hubs) thrive; those left off the network stagnate.
- Footloose capital. Mobile investment can leave a place quickly, exposing dependent regions to sudden job losses.
The core-periphery model describes a wealthy, dominant core region that concentrates power, investment and high-value activity, and a dependent periphery that supplies labour and raw materials and receives less investment. The model applies at global, national and even city scales.
Measuring spatial inequality
WACE expects you to know and interpret the main measures.
- GNI or GDP per capita: average income per person; useful for comparing countries but hides distribution within them.
- Gini coefficient: a single number from 0 (perfect equality) to 1 (one person has everything) that summarises income inequality within a population.
- Human Development Index (HDI): a UN composite of income, life expectancy and education, giving a broader picture of wellbeing than income alone.
- Choropleth and proportional maps: display how a chosen indicator varies across regions, a common stimulus skill in the examination.
The HDI runs from 0 to 1 and combines three dimensions: a long and healthy life (life expectancy), knowledge (years of schooling) and a decent standard of living (GNI per capita). Norway, Switzerland and Australia rank among the highest, while several Sub-Saharan African nations rank lowest. Because it includes more than income, the HDI can reveal inequality that GDP alone misses.
Patterns and examples
- Between countries: high-income economies in North America, Western Europe and East Asia hold a large share of global wealth, while many Sub-Saharan African and South Asian economies remain low-income. Globalisation has lifted hundreds of millions out of poverty, especially in China and India, while leaving others behind.
- Within countries: in Australia, Perth and the resource regions generate high incomes, while many remote and Indigenous communities experience much lower incomes, health and education outcomes. In China, coastal manufacturing provinces are far richer than the rural interior.
- Within cities: global cities such as London or Sydney contain both high-income financial districts and disadvantaged suburbs, a pattern visible on choropleth maps of income or disadvantage.
China's entry into global production networks from the 1980s transformed coastal cities such as Shenzhen, which grew from a fishing town into a megacity on the back of manufacturing investment and export trade. Average incomes rose dramatically. Yet the rural interior provinces saw far smaller gains, widening the gap between coastal core and inland periphery and driving huge internal migration toward the coast. This shows how the same global networks that raised national income also intensified inequality within the country, illustrating cumulative causation and the core-periphery pattern at a national scale.
Responses to spatial inequality
Governments and international bodies attempt to reduce inequality through regional development policies, infrastructure investment in peripheries, foreign aid, fair-trade schemes, the UN Sustainable Development Goals, and progressive taxation and welfare. Effectiveness varies, and a balanced answer evaluates whether such responses actually narrow the gaps.
- Analysing only one scale
- Inequality exists between countries, within countries and within cities; strong answers move between scales.
- Confusing GDP per capita with distribution
- A high average can hide deep internal inequality; that is why the Gini coefficient and HDI matter.
- Claiming globalisation only harms
- It has reduced absolute poverty for hundreds of millions while widening some relative gaps; weigh both.
- Naming measures without interpreting them
- Do not just list the HDI or Gini; explain what a given value or map pattern actually shows.
Exam-style questions
Questions in the style of SCSA exam questions on this dot point, each with a worked answer. They are written by ExamExplained unless tagged "Past paper"; the year shows the paper a question is modelled on.
WACE 2022-style12 marksAnalyse how global networks produce spatial inequalities at different scales, and evaluate one strategy used to reduce them. Use specific examples.Show worked answer →
A 12 mark response needs multi-scale analysis, the mechanisms, and an evaluated strategy.
Mechanisms. Explain how cumulative causation, value capture, connectivity and footloose capital concentrate advantage in well-connected core regions while peripheries are bypassed.
Scales. Show inequality between countries (high-income North America, Europe and East Asia versus low-income Sub-Saharan Africa), within countries (coastal versus interior China; Perth and resource regions versus remote Australia), and within cities (financial districts beside disadvantaged suburbs).
Strategy and evaluation. Choose one response, such as regional development policy, fair trade, the UN Sustainable Development Goals or progressive taxation and welfare, and judge how effectively it narrows the gap.
Markers reward movement between scales, named mechanisms and measures, and a genuine evaluation of the chosen strategy.
WACE 2024-style6 marksExplain how the Human Development Index (HDI) can reveal inequality that GDP per capita alone misses.Show worked answer →
A 6 mark response needs the composition of the HDI and the contrast with income.
Composition. The HDI runs from 0 to 1 and combines three dimensions: a long and healthy life (life expectancy), knowledge (years of schooling) and a decent standard of living (GNI per capita).
What it reveals. Because it includes health and education, the HDI captures wellbeing that an income average hides. Two countries with similar GDP per capita can have very different HDIs if one invests more in health and schooling, and a high average income can mask poor outcomes for much of a population.
Conclude that the HDI gives a broader, more human picture of development than income alone. Markers reward the three dimensions and the explicit contrast with GDP per capita.