Saturday, January 31, 2026

Plot twist: Men do read books with women protagonists

I STARTED WITH PODKAYNE OF MARS

New findings from Cornell University challenge industry assumptions about men’s reading habits and could reshape how books with women protagonists are published, promoted, and adapted.




Cornell University




ITHACA, N.Y. – In the publishing industry, there’s a common belief that men won’t read novels about women, but new research out of Cornell University finds just the opposite.

In the first large-scale study of its kind, men were equally willing to continue reading a story that featured a woman as the main character as one with a man. Women, however, showed a slight preference for reading stories about other women.

“This supposed preference among men for reading about men as characters just isn’t true. That doesn’t exist,” said Matthew Wilkens, associate professor of information science and co-author of “Causal Effect of Character Gender on Readers’ Preferences.” “That is contrary to the limited existing literature and contrary to widespread industry assumptions.”

Studies have shown that novels by men featured more male characters compared to books written by women, said Federica Bologna, a doctoral student in information science and the study’s lead author. Some previous research has suggested that men strongly prefer men as protagonists, while women will read about any gender, said Wilkens. However, these studies were practically “anecdotes” and included just a few dozen individuals. 

For the new study, the researchers recruited almost 3,000 participants – 1,492 women and 1,491 men – and asked them to read two short stories, one about a hike and another that took place at a coffee shop. Both stories’ main characters had gender-neutral names – Sam and Alex, respectively. Half of the participants were randomly assigned to read the hike story with he/him pronouns and the coffee shop story with she/her pronouns. For the other half, the pronouns were switched. After reading the two stories, participants were asked which one they wanted to keep reading.

About three-quarters of the men picked the hike story regardless of whether it featured a man or woman as the protagonist. Women, however, chose the hike story when Sam was a woman 77% of the time, but only 70% of the time when Sam was a man.

“Readers are pretty flexible,” Wilkens said. “Give them interesting stories, and they will want to read them.”

Bologna hopes this work will encourage the publishing industry to promote more books with a variety of girl and women characters.

In future work, the researchers hope to explore the preferences of nonbinary readers and to study whether the same assumptions about men’s preferences are causing creators to avoid female protagonists in other types of media, including video games.

For additional information, read this Cornell Chronicle story.

Cornell University has dedicated television and audio studios available for media interviews.

 


Collective risk resonance in Chinese stock sectors uncovered through higher-order network analysis




Shanghai Jiao Tong University Journal Center
Higher-order network construction process 

image: 

(a) Volatility of sector x_i at time t; (b) Synchronized co-movements across sectors of varying orders; (c) Pre-filtered higher-order network representation, where isolated nodes represent 0-order co-movement, gray edges indicate 1-order co-movement, yellow triangles denote 2-order co-movement, blue quadrilaterals signify 3-order co-movement, and green pentagons represent 4-order co-movement. (d) higher-order co-movement relationships retained after threshold filtering.

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Credit: Zisheng Ouyang and Yaoxun Deng (Hunan Normal University, China) Tianlei Zhu (Beijing Jiaotong University, China)





Background and Motivation

Systemic financial risk remains a critical challenge for modern economies, underscored by recurring crises such as the 2008 global financial meltdown, the 2015 Chinese stock market crash, and the COVID-19 pandemic. Traditional research has often examined sectors in isolation or focused on pairwise risk spillovers, overlooking the complex, multi-sector dependencies that can amplify systemic threats. This study addresses that gap by exploring higher-order interactions—where risks resonate simultaneously across multiple sectors—within China’s stock market. By moving beyond conventional dyadic models, the research provides a more nuanced understanding of how collective risk behaviour shapes financial stability.

 

Methodology and Scope

Using the Reconstructing the Higher Order Structure of Time Series (RHOSTS) method, the authors construct dynamic higher-order networks to capture risk co-movement among 24 Chinese stock sectors from 2007 to 2024. Sectoral volatility is estimated via GJR-GARCH models, and hyperedges represent synchronised risk resonance across multiple sectors. Network topology metrics—such as higher-order degree, systemic importance, and clustering coefficient—are analysed at both sector and system levels. The study further integrates these metrics into a coupled-map-lattice model to quantify time-varying resilience during major crises, including the 2008 financial crisis, the 2015 market crash, and the COVID-19 pandemic.

 

Key Findings and Contributions

  • Dominant Third-Order Resonance: The most prevalent risk pattern involves synchronous resonance among four sectors (third-order hyperedges), highlighting limitations of traditional pairwise models.
  • Sectoral Heterogeneity: The insurance (INS) sector consistently shows high systemic importance, while energy (ENE) becomes central during geopolitical crises like the Russia-Ukraine conflict.
  • Crisis-Specific Clusters: Core resonance groups shift with each crisis—e.g., {ENE, INS, DFI, TSE} post-2008, {TSE, RES, ACO, INS} post-2015, and {DFI, TSE, THA, SSE} post-COVID-19.
  • Network Resilience: System-wide resilience exhibits an upward long-term trend, though it fluctuates significantly during stress periods. Financial sectors generally demonstrate higher shock-absorption capacity, while retailing (RET) and capital goods (CGO) are among the most vulnerable.
  • Structural Shifts: Major events drastically alter network density, connectivity, and cluster formation, confirming that external shocks reconfigure risk transmission pathways.

 

Why It Matters

The study offers a paradigm shift in systemic risk analysis by capturing group-level risk synchronisation that traditional models miss. This approach reveals how multi-sector co-movements can accelerate contagion and create hidden vulnerabilities. By identifying crisis-specific resonance clusters and tracking resilience in real time, the research provides a more precise tool for monitoring and mitigating systemic threats in increasingly interconnected financial systems.

 

Practical Applications

  • For Regulators: Enables dynamic monitoring of higher-order risk clusters and informs targeted policies, such as cross-sector exposure limits or circuit-breaker mechanisms for highly synchronised sectors.
  • For Investors: Highlights the danger of over-concentrating portfolios in sectors prone to collective resonance—e.g., avoiding simultaneous heavy exposure to TSE, RES, ACO, and INS during turbulent periods.
  • For Risk Management: Provides a framework to design hedging strategies that account for multi-sector dependencies, particularly for energy and climate-related financial risks.
  • For Global Financial Stability: Demonstrates a scalable methodology for building real-time risk resonance surveillance systems in other markets.

 

Discover high-quality academic insights in finance from this article published in China Finance Review International. Click the DOI below to read the full-text! Open access for a limited time!