(a) Why did the Welfare Approach in Human Geography emerge as a significant perspective in 1970s? (10 marks) (b) What are the…

(a) Emergence of the Welfare Approach in Human Geography

The Welfare Approach emerged in the early 1970s as a direct critique of the Quantitative Revolution and its positivist, mechanistic spatial modeling. Spatial science had reduced human beings to rational economic points on isotropic plains, completely ignoring acute real-world crises such as poverty, territorial inequality, racial segregation, and spatial deprivation.

Catalyzed by the global "social relevance movement" and civil rights protests, geographers shifted focus from pure geometry to social justice. Pioneered by D.M. Smith through his seminal framework of "who gets what, where, and how," welfare geography redefined the discipline around human well-being, the territorial distribution of basic needs, and social indicators like healthcare, nutrition, and housing. Along with David Harvey's early transition from liberal to radical geography, this paradigm displaced value-free positivism with normative perspectives, establishing that spatial distributions of goods and "bads" are structural outcomes of socio-economic systems rather than natural market equilibriums.

(b) Challenges in Critical Minerals Extraction and Processing

Critical minerals like lithium, cobalt, nickel, and rare earth elements (REEs) are fundamental to the global green transition, yet their extraction and refining impose severe environmental and economic challenges.

Environmentally, extraction causes widespread landscape degradation, biodiversity loss, and immense water depletion. For instance, lithium brine extraction in South America's "Lithium Triangle" severely depletes hydrological basins, while REE processing generates toxic acid-mine drainage, heavy-metal contamination, and hazardous radioactive tailings, as observed in Bayan Obo, China. Cobalt mining in the Democratic Republic of Congo, which supplies about 70% of world output, is linked to artisanal mining hazards and child labour.

Economically, these minerals suffer from severe supply-chain concentration, where China accounts for roughly 60–70% of rare-earth mining and about 90% of rare-earth refining and also refines most of the world's lithium and cobalt, creating acute geopolitical dependencies and price volatility. Developing economies face the "resource curse," characterized by weak domestic value addition, high capital intensity, and Dutch disease. Furthermore, low recycling efficiency and underdeveloped circular economy frameworks fail to mitigate raw material supply shocks, endangering long-term industrial resilience. India's National Critical Mineral Mission (2025) responds by combining domestic exploration and auctions, overseas asset acquisition through KABIL, processing capacity and recycling.

(c) Perceptions versus Reality in Migration Pull Factors

Pull factors driving internal migration are fundamentally mediated through subjective cognitive maps rather than objective realities. Julian Wolpert’s concept of "Place Utility" and Everett Lee’s Push-Pull theory demonstrate that migration occurs not on actual regional wage differentials, but on the perceived net utility of destination areas.

Information asymmetry acts as a primary distortion mechanism. Return migrants and selective communication generate a remittance-driven perception gap, where consumption displays conceal exploitative working conditions, low real wages, and severe socio-spatial deprivation in destination cities. As formulated in the Harris-Todaro model, aspirational rural migrants migrate based on expected, rather than actual, urban income gains. In India, massive rural-to-urban distress migration to Tier-1 agglomerations like Mumbai and Delhi frequently confronts the reality of urban informalization, lack of social safety nets, high living costs, and subhuman existence in informal settlements like Dharavi, transforming perceived urban prosperity into persistent vulnerability.

(d) In Situ and Ex Situ Determinants of Regional Imbalances

Regional imbalances reflect the interplay between endogenous regional characteristics (in situ) and external structural interventions (ex situ), generating Gunnar Myrdal’s process of cumulative causation.

In situ factors comprise intrinsic natural resource endowments, geographical terrain, demographic profiles, and agglomeration economies. For example, coastal western states like Gujarat and Maharashtra leveraged natural port connectivity and historical merchant capital to build early industrial hubs, whereas geographically locked regions like Bundelkhand remain trapped in cyclical underdevelopment due to rugged terrain and recurrent drought.

Conversely, ex situ factors are exogenous policy distortions, external investments, and integration into national and global markets. The post-independence Freight Equalization Policy (1952) stripped the mineral-rich eastern states of Bihar, Jharkhand, and Odisha of their natural location advantages, subsidizing industrialization elsewhere. Similarly, investment concentrated in corridors such as the Delhi-Mumbai Industrial Corridor (DMIC) generates backwash effects: capital and skilled labour flow towards these nodes, while lagging interiors such as the KBK districts of Odisha send out-migrants to western and southern industrial hubs, cementing spatial dualism.

(e) Systems Analysis in Urban Planning and Its Limitations

Systems analysis conceptualizes the city not as a collection of static structures, but as a complex, open, dynamic ecosystem of interconnected subsystems, including transportation, housing, commerce, governance, and environmental infrastructure.

Its primary importance lies in mapping positive and negative feedback loops across spatial processes. Using computational simulation modeling, such as Jay Forrester’s Urban Dynamics, planners can forecast systemic ripple effects—for example, evaluating how a metro-rail investment alters peripheral land values, alters commuting modes, and impacts municipal service delivery.

However, the methodology suffers from significant limitations. First, it requires immense, high-resolution empirical data that developing cities often lack. Second, it relies on rigid mathematical assumptions of rational equilibrium, frequently failing to capture unpredictable human agency, political volatility, and informal urbanisms—such as informal settlements and unorganized street economies—which defy deterministic modeling and mechanistic top-down planning interventions. Douglass Lee's critique of large-scale urban models (1973) summarised these failures as hyper-comprehensiveness, data hunger and poor transparency.