Evolutionary dynamics of conformity
Abstract/Contents
- Abstract
- Conformist and anti-conformist cultural transmission biases have been documented in several species, in contexts from mating to finding food, and have been studied theoretically, with mathematical models. Many previous models have included a set of simplifying assumptions: (1) individuals observe a small number of cultural 'role models, ' n, and acquire a cultural variant from this sample with a single (anti-)conformity coefficient, D; (2) both n and D are constant over time; and (3) there are two cultural variants in the population (for example, the 'presence/absence' of a behavior). In Chapters 2-4, I vary each of these assumptions in turn, aiming to contribute to bridging the gap between theory and its applications to real-world scenarios. In Chapter 2, offspring can observe any number n of role models and apply different conformity rules to different configurations of sampled role models. A wide array of population dynamics emerge that were not possible in the canonical conformity model, including novel equilibria, stable cycles in variant frequencies, and chaos. In Chapter 3, n and the conformity coefficients can vary stochastically over time. This study reveals a variety of differences between deterministic and stochastic conformity models, but also proves that if conformity is expected on average in the stochastic model, the population converges to one of the three equilibria seen in the deterministic conformity model. Chapter 4 incorporates more than two cultural variants into the deterministic conformity model and uncovers novel types of polymorphic equilibria, variant frequency cycles, and chaos. Overall, Chapters 2-4 show that altering the assumptions of the standard conformity model may produce a more realistic representation of the wide range of properties that can emerge under (anti-)conformity. Chapters 5 and 6 explore how (anti-)conformity, in conjunction with other cultural transmission biases and/or genetic transmission, may affect the evolution of two phenomena—altruism and cumulative culture—that have puzzled evolutionary theorists. An altruistic behavior paradoxically reduces one's own fitness to increase that of another, and has commonly been modeled as a genetically transmitted trait. Chapter 5 shows how cultural transmission of altruism, including conformity, anti-conformity, and a "content" bias for altruistic behavior, changes the conditions under which this behavior evolves compared to those under purely genetic transmission. Chapter 6 seeks to explain why cumulative culture, i.e., the incremental improvement of a cultural trait, such as a tool, over time, is seen in few non-human animals despite its potential advantages. Results show that small population sizes and conformist transmission can hinder cultural accumulation.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Denton, Kaleda Krebs |
|---|---|
| Degree supervisor | Feldman, Marcus W |
| Thesis advisor | Feldman, Marcus W |
| Thesis advisor | Rosenberg, Noah |
| Thesis advisor | Tuljapurkar, Shripad, 1951- |
| Degree committee member | Rosenberg, Noah |
| Degree committee member | Tuljapurkar, Shripad, 1951- |
| Associated with | Stanford University, School of Humanities and Sciences |
| Associated with | Stanford University, Department of Biology |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Kaleda Krebs Denton. |
|---|---|
| Note | Submitted to the Department of Biology. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/pv729wb0352 |
Access conditions
- Copyright
- © 2023 by Kaleda Krebs Denton
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...