What information do citizens want? Evidence from one million information requests in Mexico

While scholars have emphasized the importance of information for accountability, little research has addressed the demand for government information by real citizens. We study the totality of information requests filed with Mexican federal government agencies from 2003 to 2015, over 1 million requests in all. We use unsupervised methods to categorize requests, revealing the diversity of topics including environment, security, budgets, and government procurement and employees. While many topics have clear public accountability-seeking purposes, others are focused on more private, micro-political goals. Analysis over time and across states reveals linkage between information demand and issues of public interest such as environmental impacts and criminal violence. Our results demonstrate that, given functioning access-to-information institutions, citizens in a transitional democracy really do demand information relevant to public accountability

The political logic of government disclosure: evidence from information requests in Mexico

When citizens ask questions, how does their government answer? Requests for government information confront officials with incentives both for and against disclosure. We argue that officials seek to manage political risks in ways that favor requests from government-aligned regions. We study responsiveness in the context of Mexico’s access-to-information law, using publicly available data from several hundred thousand information requests filed with Mexican federal government agencies between 2003 and 2015. Our empirical strategy makes comparisons only among requests sent to similar agencies on similar topics at similar times, while accounting for the complexity, sophistication, and sensitivity of individual requests. We find that requests filed from locales with higher governing-party vote shares receive more favorable responses, across multiple indicators of the nature and timing of responses. Further, we find bias only for requests on publicly relevant topics, providing evidence in favor of a mechanism of mitigating political risks over one of rewarding supporters with greater access to benefits

Media attention and bureaucratic responsiveness

How does media attention shape bureaucratic behavior? We answer this question using novel data from the Mexican federal government. We first develop a new indicator for periods of anomalously heightened media attention, based on 150,000 news articles pertaining to 22 Mexican government ministries and agencies, and qualitatively categorize their themes. We then evaluate government responsiveness using administrative data on roughly 500,000 requests for government information over a 10-year period, with their associated responses. A panel fixed-effects approach demonstrates effects of media attention on the volume of outgoing weekly responses, while a second approach finds effects on the “queue” of information requests already filed when anomalous media attention begins. Consistent across these empirical approaches, we find that media attention shapes bureaucratic behavior. Positive or neutral attention is associated with reduced responsiveness, while the effects of negative attention vary, with attention to government failures leading to increased responsiveness but attention to corruption leading to reduced responsiveness. These patterns are consistent with mechanisms of reputation management, disclosure threat, and workload burden, but inconsistent with mechanisms of credit claiming or blame avoidance

Inferring Phylogenies from RAD Sequence Data

Reduced-representation genome sequencing represents a new source of data for systematics, and its potential utility in interspecific phylogeny reconstruction has not yet been explored. One approach that seems especially promising is the use of inexpensive short-read technologies (e.g., Illumina, SOLiD) to sequence restriction-site associated DNA (RAD) – the regions of the genome that flank the recognition sites of restriction enzymes. In this study, we simulated the collection of RAD sequences from sequenced genomes of different taxa (Drosophila, mammals, and yeasts) and developed a proof-of-concept workflow to test whether informative data could be extracted and used to accurately reconstruct “known” phylogenies of species within each group. The workflow consists of three basic steps: first, sequences are clustered by similarity to estimate orthology; second, clusters are filtered by taxonomic coverage; and third, they are aligned and concatenated for “total evidence” phylogenetic analysis. We evaluated the performance of clustering and filtering parameters by comparing the resulting topologies with well-supported reference trees and we were able to identify conditions under which the reference tree was inferred with high support. For Drosophila, whole genome alignments allowed us to directly evaluate which parameters most consistently recovered orthologous sequences. For the parameter ranges explored, we recovered the best results at the low ends of sequence similarity and taxonomic representation of loci; these generated the largest supermatrices with the highest proportion of missing data. Applications of the method to mammals and yeasts were less successful, which we suggest may be due partly to their much deeper evolutionary divergence times compared to Drosophila (crown ages of approximately 100 and 300 versus 60 Mya, respectively). RAD sequences thus appear to hold promise for reconstructing phylogenetic relationships in younger clades in which sufficient numbers of orthologous restriction sites are retained across species.</p

Fine Grid Numerical Solutions of Triangular Cavity Flow

Numerical solutions of 2-D steady incompressible flow inside a triangular cavity are presented. For the purpose of comparing our results with several different triangular cavity studies with different triangle geometries, a general triangle mapped onto a computational domain is considered. The Navier-Stokes equations in general curvilinear coordinates in streamfunction and vorticity formulation are numerically solved. Using a very fine grid mesh, the triangular cavity flow is solved for high Reynolds numbers. The results are compared with the numerical solutions found in the literature and also with analytical solutions as well. Detailed results are presented

Multi-label prediction for political text-as-data

Political scientists increasingly use supervised machine learning to code multiple relevant labels from a single set of texts. The current "best practice"of individually applying supervised machine learning to each label ignores information on inter-label association(s), and is likely to under-perform as a result. We introduce multi-label prediction as a solution to this problem. After reviewing the multi-label prediction framework, we apply it to code multiple features of (i) access to information requests made to the Mexican government and (ii) country-year human rights reports. We find that multi-label prediction outperforms standard supervised learning approaches, even in instances where the correlations among one's multiple labels are low

Measuring human rights abuse from access to information requests

Existing measures of human rights abuses are often only available at the country-year level. Several more fine-grained measures exhibit spatio-temporal inaccuracies or reporting biases due to the primary sources upon which they rely. To address these challenges, and to increase the diversity of available human rights measures more generally, this study provides the first quantitative effort to measure human rights abuses from textual records of citizen-government interactions. Using a dataset encompassing over 1.5 million access-to-information (ATI) requests made to the Mexican federal government from June 2003 onward, supervised classification is used to identify the subset of these requests that pertain to human rights abuses of various types. The results from this supervised machine learning exercise are validated against (i) gold standard ATI requests pertaining to past human rights abuses in Mexico and (ii) several accepted external measures of sub-national and sub-annual human rights abuses. In doing so, we demonstrate that the measurement of human rights abuses from citizen-submitted ATI request texts can provide measures of human rights abuse that exhibit both high validity and notable spatio-temporal specificity, relative to existent human rights datasets and variables

Bacterial Infections across the Ants: Frequency and Prevalence of Wolbachia, Spiroplasma

Bacterial endosymbionts are common across insects, but we often lack a deeper knowledge of their prevalence across most organisms. Next-generation sequencing approaches can characterize bacterial diversity associated with a host and at the same time facilitate the fast and simultaneous screening of infectious bacteria. In this study, we used 16S rRNA tag encoded amplicon pyrosequencing to survey bacterial communities of 310 samples representing 221 individuals, 176 colonies and 95 species of ants. We found three distinct endosymbiont groups—Wolbachia (Alphaproteobacteria: Rickettsiales), Spiroplasma (Firmicutes: Entomoplasmatales), and relatives of Asaia (Alphaproteobacteria: Rhodospirillales)—at different infection frequencies (at the ant species level: 22.1%, 28.4%, and 14.7%, resp.) and relative abundances within bacterial communities (1.0%–99.9%). Spiroplasma was particularly enriched in the ant genus Polyrhachis, while Asaia relatives were most prevalent in arboreal ants of the genus Pseudomyrmex. While Wolbachia and Spiroplasma have been surveyed in ants before, Asaia, an acetic acid bacterium capable of fixing atmospheric nitrogen, has received much less attention. Due to sporadic prevalence across all ant taxa investigated, we hypothesize facultative associations for all three bacterial genera. Infection patterns are discussed in relation to potential adaptation of specific bacteria in certain ant groups

Investigating the Impact of Storage Conditions on Microbial Community Composition in Soil Samples

Recent advances in DNA sequencing technologies have allowed scientists to probe increasingly complex biological systems, including the diversity of bacteria in the environment. However, despite a multitude of recent studies incorporating these methods, many questions regarding how environmental samples should be collected and stored still persist. Here, we assess the impact of different soil storage conditions on microbial community composition using Illumina-based 16S rRNA V4 amplicon sequencing. Both storage time and temperature affected bacterial community composition and structure. Frozen samples maintained the highest alpha diversity and differed least in beta diversity, suggesting the utility of cold storage for maintaining consistent communities. Samples stored for intermediate times (three and seven days) had both the highest alpha diversity and the largest differences in overall beta diversity, showing the degree of community change after sample collection. These divergences notwithstanding, differences in neither storage time nor storage temperature substantially altered overall communities relative to more than 500 previously examined soil samples. These results systematically support previous studies and stress the importance of methodological consistency for accurate characterization and comparison of soil microbiological assemblages.</p