Measuring Hidden Opinions in Iran and China
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| Format: | Recurso digital |
| Sprache: | Englisch |
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2026
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| _version_ | 1866901593537904640 |
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| author | Rosehill, Daniel Gemini 3.1 (Flash) Chatterbox TTS |
| author_facet | Rosehill, Daniel Gemini 3.1 (Flash) Chatterbox TTS |
| contents | <p><strong>Episode summary:</strong> How do you measure public sentiment when the state controls the information environment and people fear honest answers? This episode explores the surprisingly robust data coming out of Iran through GAMAAN's digital snowball sampling, which found only 15% of Iranians support the Islamic Republic as a system of government. Then we turn to China, where the measurement problem is even harder. Through academic surveys, the Asian Barometer, World Values Survey, and clever list experiments that provide plausible deniability to respondents, researchers have pieced together a picture of broad but shallow and conditional support for the regime — with fascinating cleavages by age, geography, and education that defy both Western narratives of imminent collapse and Party claims of universal loyalty.</p> <h3>Show Notes</h3> <p>Measuring public opinion in authoritarian states is one of the hardest problems in political science. This episode examines two case studies — Iran and China — where researchers have developed creative methods to gauge real sentiment despite state control of the information environment.</p> <p>In Iran, the Group for Analyzing and Measuring Attitudes in Iran (GAMAAN) has used digital snowball sampling — viral survey distribution through social media — to reach deep into the population. Their 2022 survey found only about 15% of Iranians identifying as Shia Muslims who support the political establishment, with support for the Islamic Republic as a system of government around 20% and support for the Revolutionary Guard in single digits. Methodological cross-referencing against pre-crackdown face-to-face surveys and diaspora polling suggests the data is reliable.</p> <p>For China, no gold-standard representative polling exists, but researchers have four main windows: academic collaborations like the China Survey, the Asian Barometer Survey, the World Values Survey, and list experiments that provide plausible deniability. The evidence suggests broad but shallow and conditional support — high performance satisfaction on economic growth and stability, but complex attitudes on democratic values. Younger Chinese under 35 are notably more nationalist than their parents' generation, while the urban-rural split runs counter to expectations: urban residents benefit most from regime policies while rural residents maintain high trust in the central government while blaming local officials for problems.</p> <p>Listen online: <a href="https://myweirdprompts.com/episode/measuring-hidden-opinions-iran-china">https://myweirdprompts.com/episode/measuring-hidden-opinions-iran-china</a></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20243361 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Measuring Hidden Opinions in Iran and China Rosehill, Daniel Gemini 3.1 (Flash) Chatterbox TTS podcast ai-generated my weird prompts iran list-experiments political-measurement <p><strong>Episode summary:</strong> How do you measure public sentiment when the state controls the information environment and people fear honest answers? This episode explores the surprisingly robust data coming out of Iran through GAMAAN's digital snowball sampling, which found only 15% of Iranians support the Islamic Republic as a system of government. Then we turn to China, where the measurement problem is even harder. Through academic surveys, the Asian Barometer, World Values Survey, and clever list experiments that provide plausible deniability to respondents, researchers have pieced together a picture of broad but shallow and conditional support for the regime — with fascinating cleavages by age, geography, and education that defy both Western narratives of imminent collapse and Party claims of universal loyalty.</p> <h3>Show Notes</h3> <p>Measuring public opinion in authoritarian states is one of the hardest problems in political science. This episode examines two case studies — Iran and China — where researchers have developed creative methods to gauge real sentiment despite state control of the information environment.</p> <p>In Iran, the Group for Analyzing and Measuring Attitudes in Iran (GAMAAN) has used digital snowball sampling — viral survey distribution through social media — to reach deep into the population. Their 2022 survey found only about 15% of Iranians identifying as Shia Muslims who support the political establishment, with support for the Islamic Republic as a system of government around 20% and support for the Revolutionary Guard in single digits. Methodological cross-referencing against pre-crackdown face-to-face surveys and diaspora polling suggests the data is reliable.</p> <p>For China, no gold-standard representative polling exists, but researchers have four main windows: academic collaborations like the China Survey, the Asian Barometer Survey, the World Values Survey, and list experiments that provide plausible deniability. The evidence suggests broad but shallow and conditional support — high performance satisfaction on economic growth and stability, but complex attitudes on democratic values. Younger Chinese under 35 are notably more nationalist than their parents' generation, while the urban-rural split runs counter to expectations: urban residents benefit most from regime policies while rural residents maintain high trust in the central government while blaming local officials for problems.</p> <p>Listen online: <a href="https://myweirdprompts.com/episode/measuring-hidden-opinions-iran-china">https://myweirdprompts.com/episode/measuring-hidden-opinions-iran-china</a></p> |
| title | Measuring Hidden Opinions in Iran and China |
| topic | podcast ai-generated my weird prompts iran list-experiments political-measurement |
| url | https://doi.org/10.5281/zenodo.20243361 |