Purpose of Addressing Aggregation Risk
This article explains the risks associated with aggregating residential data in Lagos-related content. Its purpose is to define why aggregation can distort interpretation and to establish boundaries on how aggregated representations should be read.
Aggregation as a Loss of Context
Aggregation combines individual residential listings or references into broader groupings such as districts, zones, or categories. While aggregation may simplify presentation, it removes contextual detail about individual listings, spatial nuance, and labeling variability that is essential for accurate understanding.
Heterogeneity Within Aggregated Units
Residential districts and spatial groupings in Lagos are internally heterogeneous. Aggregated representations collapse diverse residential forms, labeling practices, and spatial conditions into single units, obscuring internal variation without indicating uniformity or coherence.
Interaction With Listing-Based Visibility
Because listing data reflects visibility rather than comprehensive coverage, aggregation amplifies visibility bias. Areas or categories with higher platform participation may dominate aggregated views, while less visible segments are further obscured through combination.
Misleading Patterns From Aggregation
Apparent patterns that emerge from aggregated residential data often reflect grouping choices rather than underlying residential realities. Such patterns should not be interpreted as distributions, concentrations, or structural characteristics of Lagos residential environments.
Interpretive Boundaries
This article establishes firm limits on aggregation-based interpretation. Aggregated residential data does not support inference, comparison, prioritization, or evaluation. It functions as a presentation convenience, not as an analytical representation.