arXiv subjects

Matthew G. Burgess

Publications and source records attributed to Matthew G. Burgess.

5 recordsLinked to original sources

arXiv2026

Can homophily explain public underestimation of climate policy support?

Many climate change mitigation policies enjoy large majority support from the U.S. public. Yet, both Republicans and Democrats underestimate public support for climate policies, on average, with Republicans underestimating by more. Explaining this is a major puzzle in climate change politics. Homophily is one possible explanation: if citizens are selectively exposed to views reinforcing their own, then policy opponents might underestimate support more than supporters. Here, we explore how homophily could interact with social network structure to produce misperceptions of policy support, using a stochastic block model and preferential attachment model. Homophily alone can explain opponents underestimating support by more than supporters, but supporters only underestimate support when their homophily is so low that they disproportionately associate with opponents. We then expand our model to combine homophily with Bayesian rescaling, inaccurate priors, or asymmetric prominence of opposing opinions (simulating media bias). With Bayesian rescaling and inaccurate priors, homophily would still need to be highly asymmetric to produce realistic misperception patterns. Media bias combined with realistic, symmetric homophily can produce realistic misperception patterns in our model. However, empirical evidence on media bias in coverage of climate change policy is mixed. Our analyses provide theoretical foundations for advancing understanding of public opinion misperception, on climate change and other issues.

physics.soc-ph↗

arXiv2026

Optimal ambition in business, politics and life

In business, politics and life, folk wisdom encourages people to aim for above-average results, but to not let the perfect be the enemy of the good. Here, we mathematically formalize and extend this folk wisdom. We model a time-limited search for strategies having uncertain rewards. At each time step, the searcher either is satisfied with their current reward or continues searching. We prove that the optimal satisfaction threshold is both finite and strictly larger than the mean of available rewards -- matching the folk wisdom. This result is robust to search costs, unless they are high enough to prohibit all search. We show that being too ambitious has a higher expected cost than being too cautious. We show that the optimal satisfaction threshold increases if the search time is longer, or if the reward distribution is rugged (i.e., has low autocorrelation) or left-skewed. The skewness result reveals counterintuitive contrasts between optimal ambition and optimal risk taking. We show that using upward social comparison to assess the reward landscape substantially harms expected performance. We show how these insights can be applied qualitatively to real-world settings, using examples from entrepreneurship, economic policy, political campaigns, online dating and college admissions. We discuss implications of several possible extensions of our model, including intelligent search, reward landscape uncertainty and risk aversion.

physics.soc-ph↗

arXiv2021

Empirically Classifying Network Mechanisms

Network models are used to study interconnected systems across many physical, biological, and social disciplines. Such models often assume a particular network-generating mechanism, which when fit to data produces estimates of mechanism-specific parameters that describe how systems function. For instance, a social network model might assume new individuals connect to others with probability proportional to their number of pre-existing connections ('preferential attachment'), and then estimate the disparity in interactions between famous and obscure individuals with similar qualifications. However, without a means of testing the relevance of the assumed mechanism, conclusions from such models could be misleading. Here we introduce a simple empirical approach which can mechanistically classify arbitrary network data. Our approach compares empirical networks to model networks from a user-provided candidate set of mechanisms, and classifies each network--with high accuracy--as originating from either one of the mechanisms or none of them. We tested 373 empirical networks against five of the most widely studied network mechanisms and found that most (228) were unlike any of these mechanisms. This raises the possibility that some empirical networks arise from mixtures of mechanisms. We show that mixtures are often unidentifiable because different mixtures can produce functionally equivalent networks. In such systems, which are governed by multiple mechanisms, our approach can still accurately predict out-of-sample functional properties.

cs.SI↗

arXiv2017

Range contraction enables harvesting to extinction

Economic incentives to harvest a species usually diminish as its abundance declines, because harvest costs increase. This prevents harvesting to extinction. A known exception can occur if consumer demand causes a declining species' harvest price to rise faster than costs. This threat may affect rare and valuable species, such as large land mammals, sturgeons, and bluefin tunas. We analyze a similar but underappreciated threat, which arises when the geographic area (range) occupied by a species contracts as its abundance declines. Range contractions maintain the local densities of declining populations, which facilitates harvesting to extinction by preventing abundance declines from causing harvest costs to rise. Factors causing such range contractions include schooling, herding, or flocking behaviors--which, ironically, can be predator-avoidance adaptations; patchy environments; habitat loss; and climate change. We use a simple model to identify combinations of range contractions and price increases capable of causing extinction from profitable overharvesting, and we compare these to an empirical review. We find that some aquatic species that school or forage in patchy environments experience sufficiently severe range contractions as they decline to allow profitable harvesting to extinction even with little or no price increase; and some high-value declining aquatic species experience severe price increases. For terrestrial species, the data needed to evaluate our theory are scarce, but available evidence suggests that extinction-enabling range contractions may be common among declining mammals and birds. Thus, factors causing range contraction as abundance declines may pose unexpectedly large extinction risks to harvested species.

q-bio.PE↗

arXiv2014

Consequences of fleet diversification in managed and unmanaged fisheries

Biological diversity is known to play an important role in generating and maintaining ecosystem productivity and other functions, and has consequently become a central focus of many efforts to preserve ecosystem services. Theoretical parallels suggest the diversity of fishing fleets may have a similarly important role in determining the productivity and ecological impacts of fisheries, but this possibility has rarely been explored. Here I present theoretical analyses showing that the diversity of métiers - combinations of technology, target species, and fishing grounds - and technical efficiencies in a fishing fleet have important impacts on the productivity, profitability, and ecological impacts of fisheries, particularly mixed-stock or multispecies fisheries. Diversification of métiers can increase yields and reduce threats to weak stocks in both managed and unmanaged multispecies fisheries. Diversification of technical efficiencies creates opportunities for larger profits in managed fisheries, but often decreases yields and worsens impacts on weak stocks in unmanaged fisheries. These results suggest that the potential impact of management may be highest in fisheries with diverse fleets.

q-bio.PE↗