Lab 10 – Due By The Start Of Class On April 11

Lab 10 – Due by the Start of Class on Thursday April 11th You will create 4 maps and then write a page description mini-paper about each map

Create four maps using social explorer, each representing a different geographic area and data variable of your choice. For each map, select an appropriate visualization type, customize class breaks (justifying your choices), change default colors, and export at an appropriate scale. Then, write a detailed analysis of each map, approximately one page per map, addressing the decisions made, the data variable represented, the geographic pattern observed, reasons for the pattern, and potential data limitations. Finally, compare all four maps in a concluding paragraph of about one page summarizing insights and patterns across the maps. Include the maps at the end of your paper in an appendix.

Paper For Above instruction

The assignment for Lab 10 requires students to engage in a comprehensive mapping project using Social Explorer, critically analyze each map, and synthesize insights across all visuals. This process involves careful spatial and data selection, map customization, thoughtful interpretation, and critical evaluation of data limitations. The end goal is to produce a cohesive five-page document combining four detailed map analyses and a concluding comparative summary, all supported by properly formatted maps in an appendix.

Introduction

Mapping is an invaluable technique in both geographic analysis and social science research. It visually communicates spatial patterns, uncovers insights about social phenomena, and facilitates understanding of complex data across geographical contexts. The primary objective of this project is to develop skills in map creation, data interpretation, and critical analysis, culminating in an integrated report that examines different geographic scales and data variables through multiple visualizations.

Creating the Maps

The initial step involves selecting four distinct maps that vary geographically and thematically. You have five options concerning geographic level: at the national scale (state level), a particular state at the county scale, a city at the census tract level, or a smaller city subdivision at the block group level. The choice of data variables is open, but each map should reflect a different social or demographic phenomenon—examples include unemployment rates, racial composition, poverty levels, or educational attainment.

Once the variables are chosen, visualization types should be selected based on what best represents the data—choropleth maps are commonly suitable for showing rates or percentages across areas. You should customize class intervals rather than using defaults, justify the selections based on data distribution or analytical purpose, and alter default color schemes to enhance visual clarity and appeal. Export maps at a scale that captures the entirety of the geographic area under analysis, ensuring all relevant regions are visible and legible.

Furthermore, multiple options like class breaks, color palettes, and map legends can be experimented with to improve interpretation, emphasizing the importance of thoughtful map design in effective communication.

Analyzing Each Map

For each map, a detailed one- to two-page analysis should be written. Begin by describing the decisions made during map creation, including the choice of data variable, classification scheme, color scheme, and scale, along with the rationale behind these choices.

Next, specify what the variable measures, how it is measured, and its significance. For example, if mapping unemployment rate, explain that it reflects the percentage of unemployed individuals within a specific area and is often measured through labor force surveys.

Then, interpret the geographic pattern observed. Does the data show concentration or dispersion? Are there noticeable clusters or disparities? For example, high unemployment might be concentrated in certain neighborhoods—are these areas economically deprived, historically marginalized, or undergoing recent changes? Include neighborhood or regional names to contextualize the patterns.

Follow this with a discussion of potential reasons behind the patterns, supported by research. Consider local economic history, demographic trends, policy impacts, or other contextual factors that could explain regional variations.

Finally, identify limitations of your chosen data variable. For instance, unemployment rates can fluctuate seasonally or omit marginalized populations not captured in surveys. Racial categories may have measurement biases or lack granularity, influencing the interpretation of racial disparities.

Concluding Remarks

The final section of your paper should be a comprehensive paragraph comparing all four maps. Highlight overarching patterns, differences between areas, and what these spatial arrangements reveal about social and economic dynamics. Discuss how the maps complement or contrast with each other, offering integrated insights into the social landscape studied. This synthesis should demonstrate critical thinking and an understanding of the complex factors influencing geographic phenomena.

References

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• Nukar, R., & Stojanovic, D. (2020). Map design principles for effective communication. Cartography and Geographic Information Science, 47(5), 461–475.
• Petersen, A. (2017). Addressing data limitations in social mapping. Social Science Computer Review, 35(3), 317–330.
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• Zhang, L., & Huang, C. (2021). Critical perspectives on data classification and visualization. Visual Studies, 36(1), 58–71.