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subjective.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Subjective Variables in Social Science</title>
<link rel="stylesheet" href="subjective.css">
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<body>
<header>
<div class="header-container">
<h1>Subjective Variables in Social Science</h1>
<p class="subtitle">The Influence of Weighted Variables on Perceptions of Well-being</p>
</div>
</header>
<section id="introduction">
<p>
The World Happiness Report, with its emphasis on variables like social support, presents a compelling framework for evaluating well-being. However, assigning such a significant weight to social support raises questions about the subjectivity inherent in this process. To what extent can the subjective experience of "social support" reliably measure national happiness, and who decides the importance of this variable compared to others?
</p>
<p>
While on the surface, emphasizing social support as a key happiness metric seems reasonable, it’s useful to consider how earlier statistical methods weighed variables according to their perceived social value. Historical approaches, such as those by early 20th-century statisticians, assigned weight to variables like intelligence or race, reflecting their beliefs about what constituted societal progress. Although modern variables differ, the underlying process of choosing and weighting them shares a common thread with past methodologies.
</p>
</section>
<!-- Radial Tree Diagram Section -->
<section id="radial-tree">
<h2>Visualizing Variable Weighting Over Time</h2>
<div id="tree-container"></div>
</section>
<section id="analysis">
<p>
This visualization invites us to consider how the weighting of variables has evolved over time, shifting from biologically deterministic factors like intelligence and race, to broader socio-economic variables such as GDP and social support. While modern frameworks like the World Happiness Report may appear more inclusive, they are still products of subjective choices. The prioritization of variables in any model reflects the biases, cultural values, and assumptions of those who create it.
</p>
<p>
By comparing these shifting priorities, we see a clear connection between today’s well-being metrics and past methodologies that sought to categorize people based on subjective judgments. Just as intelligence and race once carried the weight of 'social progress,' today's variables like social support carry the weight of 'happiness.' This continuity prompts reflection on the degree to which these measures—however well-intentioned—are shaped by prevailing cultural norms and ideological perspectives, rather than objective truths.
</p>
</section>
<footer>
<p>© 2024 Colin Geraghty. All rights reserved.</p>
</footer>
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children: [
{ name: "1920s", children: [{ name: "Race" }, { name: "Intelligence" }] },
{ name: "1960s", children: [{ name: "GDP" }, { name: "Economic Output" }] },
{ name: "2000s", children: [{ name: "Social Support" }, { name: "Life Satisfaction" }] },
{ name: "2020s", children: [{ name: "Environmental Quality" }, { name: "Well-being" }] }
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