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研究方法

Durable majority gerrymanders: Where partisan gerrymandering can displace democracy

·586 字·2 分钟
Polihot 美国政治 研究方法 Gerrymandering Redistricting State Legislatures Democracy Electoral Geography
AJPS — 2026-08-10 Original Durable majority gerrymanders: Where partisan gerrymandering can displace democracy Maxwell Palmer, Benjamin Schneer Abstract Abstract We develop the concept of, and estimation tools for, durable majority gerrymanders : electoral district maps drawn to reduce an opposing political party's probability of winning a majority in a legislative chamber. Directly interpretable, forward‐looking, and motivated by the democratic principle that a party in power should have some chance of losing it, this measure provides new insights into the role of redistricting in state legislative elections. We show that, when map drawers are unconstrained, the ability to create durable majorities is so widespread that at least one party in every state can draw a map where a majority of legislative districts withstand almost any likely future electoral swing. Enacted maps are less durable due to a combination of underlying geography, voter partisanship, and state‐level guidelines. This paper provides the theoretical framework and empirical tools to understand which gerrymandered maps enable state‐level majorities to emerge and to endure.

Is Blood Thicker Than Water(-and-Earth)? Partisanship Geography in Imperial China and the Limits of Quantitative History

·513 字·2 分钟
Polihot 比较政治 研究方法 中国研究 Historical Political Economy Replication Imperial China Kinship Networks Wang Anshi Reform
APSR — pp. 1-12 2026-07-29 Original Is Blood Thicker Than Water(-and-Earth)? Partisanship Geography in Imperial China and the Limits of Quantitative History YAO LIN Abstract Using Wang Anshi’s Reform as a case study, Yuhua Wang’s “Blood is Thicker Than Water” ( American Political Science Review , 2022) argues that geographically dispersed kinship networks incentivize political elites to support the building of a strong state, whereas geographically concentrated kinship networks undermine state building. In this article, I improve the sample with the help of additional historical records and show that the reported correlation fails to replicate when either the control issue or the outlier issue is considered. I then propose two alternative hypotheses on the role of kinship network dispersal in Wang Anshi’s Reform, based on two common explanations of its partisanship geography in Chinese historical scholarship, that is, status competition and policy adaptiveness. After examining those hypotheses respectively, I reflect on the limits of quantitative history that this case illustrates.

Still Instrumentally Inclusive

·620 字·2 分钟
Polihot 政治行为 研究方法 LGBT+ Inclusion Homonationalism Immigration Attitudes Survey Experiment Replication
APSR — pp. 1-9 2026-07-28 Original Still Instrumentally Inclusive STUART J. TURNBULL-DUGARTE, ALBERTO LÓPEZ ORTEGA Abstract Do individuals in Western democracies shift their views on LGBT+ inclusion when exposed to opposition from Muslim out-groups? And is this “homonationalist” responsiveness stronger among anti-immigration individuals? Our article “Instrumentally inclusive [...]” addressed these questions using representative data from Britain (Study 1) and crowd-sourced data from Spain (Study 2). We revisit Study 2 in response to concerns about post-stratification weighting a convenience sample and erroneously inconsistent use of robust standard errors. Varying population reference parameters, weight caps, variance estimators, subgroup definitions, and covariate adjustments, we find strong support for the original findings. Neither reasonable alternative weighting schemes nor corrected variance estimators substantively change the results. In fact, the originally published point estimates are equal to or smaller than the median across alternative specifications. Consistent with the Article, we find that treatment increases support for LGBT+ inclusion in Spain, without consistent identifiable variation by immigration attitudes.

When coordination is avoidable: A monotonicity analysis of organizational tasks

·635 字·2 分钟
Polihot 公共行政 研究方法 LLM相关 Coordination Organizational Tasks Monotonicity Multiagent AI Interdependence
PNAS 123/31 pp. e2606267123-e2606267123 2026-07-27 Original When coordination is avoidable: A monotonicity analysis of organizational tasks Harang Ju Abstract Organizations devote substantial resources to coordination, yet which tasks actually require it for correctness remains unclear. The problem is acute in multiagent AI systems, where coordination cost is directly measurable and can exceed the cost of the work itself. Distributed systems theory provides a precise criterion: Coordination is required when a task specification is nonmonotonic, meaning that as histories grow, new information can invalidate prior conclusions. Here we show that Thompson's classic taxonomy of interdependence maps to that criterion, yielding a decision rule for when coordination is required for correctness. We formalize the correspondence in a bridge theorem, apply the rule to 65 workflows from the American Productivity & Quality Center (APQC), and (with a calibrated large language model (LLM), 13,417 Occupational Information Network (O*NET tasks), and illustrate it in multiagent AI simulations. Under our decompositions, 74% of workflows and 42% of O*NET tasks are monotonic, implying that up to 24 to 57% of coordination spending is unnecessary for correctness.

Correcting measurement error bias in conjoint survey experiments

·487 字·1 分钟
Polihot 研究方法 Conjoint Experiments Measurement Error Survey Experiments Bias Correction Causal Inference
AJPS — 2026-07-23 Original Correcting measurement error bias in conjoint survey experiments Katherine Clayton, Yusaku Horiuchi, Aaron R. Kaufman, Gary King, Mayya Komisarchik Abstract Abstract Conjoint survey designs are spreading across the social sciences due to their unusual capacity to estimate many causal effects from a single randomized experiment. Unfortunately, by their ability to mirror complicated real‐world choices, these designs often generate substantial measurement error and thus bias. We replicate both the data collection and analysis from eight prominent conjoint studies, all of which closely reproduce published results, and reveal high levels of measurement error in all. We then discover a common empirical pattern in how measurement error appears in conjoint studies and, with it, introduce an easy‐to‐use statistical method to correct the bias. Along the way, we provide a much simpler and simultaneously more powerful approach to designing, organizing, understanding, and analyzing conjoint data analyses.