Do children copy an expert or a majority? Examining selective learning in instrumental and normative contexts

This study examined whether instrumental and normative learning contexts differentially influence 4- to 7-year-old children’s social learning strategies; specifically, their dispositions to copy an expert versus a majority consensus. Experiment 1 (N = 44) established that children copied a relatively competent “expert” individual over an incompetent individual in both kinds of learning context. In experiment 2 (N = 80) we then tested whether children would copy a competent individual versus a majority, in each of the two different learning contexts. Results showed that individual children differed in strategy, preferring with significant consistency across two different test trials to copy either the competent individual or the majority. This study is the first to show that children prefer to copy more competent individuals when shown competing methods of achieving an instrumental goal (Experiment 1) and provides new evidence that children, at least in our “individualist” culture, may consistently express either a competency or majority bias in learning both instrumental and normative information (Experiment 2). This effect was similar in the instrumental and normative learning contexts we applied.

Environmental Policy in Majoritarian Systems

This paper sheds new light on the determination of environmental policies in majoritarian federal electoral systems such as the U.S., and derives implications for the environmental federalism debate on whether the national or local government should have authority over environmental policies. In majoritarian systems, where the legislature consists of geographically distinct electoral districts, the majority party (at either the national or the state level) favors its own home districts; depending on the location of polluting industries and the associated pollution damages, the majority party may therefore impose sub-optimally high or low pollution taxes due to a majority bias. We show that majority bias can influence the social-welfare ranking of alternative government policies and, in some cases, may actually bring distortionary policies closer to the first-best solution.

On food security and alternative food networks: Understanding and performing food security in the context of urban bias

This paper offers one explanation for the institutional basis of food insecurity in Australia, and argues that while alternative food networks and the food sovereignty movement perform a valuable function in building forms of social solidarity between urban consumers and rural producers, they currently make only a minor contribution to Australia’s food and nutrition security. The paper begins by identifying two key drivers of food security: household incomes (on the demand side) and nutrition-sensitive, ‘fair food’ agriculture (on the supply side). We focus on this second driver and argue that healthy populations require an agricultural sector that delivers dietary diversity via a fair and sustainable food system. In order to understand why nutrition-sensitive, fair food agriculture is not flourishing in Australia we introduce the development economics theory of urban bias. According to this theory, governments support capital intensive rather than labour intensive agriculture in order to deliver cheap food alongside the transfer of public revenues gained from rural agriculture to urban infrastructure, where the majority of the voting public resides. We chart the unfolding of the Urban Bias across the twentieth century and its consolidation through neo-liberal orthodoxy, and argue that agricultural policies do little to sustain, let alone revitalize, rural and regional Australia. We conclude that by observing food system dynamics through a re-spatialized lens, Urban Bias Theory is valuable in highlighting rural–urban socio-economic and political economy tensions, particularly regarding food system sustainability. It also sheds light on the cultural economy tensions for alternative food networks as they move beyond niche markets to simultaneously support urban food security and sustainable rural livelihoods.

Analysis of avalanche breakdown in bipolar transistors based on majority carrier transportation

This paper describes a new analysis of the avalanche breakdown phenomenon in bipolar transistors for different bias conditions of the emitter-base junction. This analysis revolves around the transportation and storage of majority carriers in the base region. Using this analysis one can compute all the voltage-current characteristics of a transistor under avalanche breakdown.

Investigation on the origin of exchange bias in epitaxial, oriented and polycrystalline Fe3O4 thin films

We observe exchange bias (EB) in a single magnetic film Fe3O4 at temperature T < 200 K. Irrespective of crystallographic orientations of grown Fe3O4; they exhibit similar nature of EB for (100) epitaxial, (111) oriented and polycrystalline Fe3O4 thin films. Growth induced defects such as anti-phase boundaries (APBs) in epitaxial Fe3O4 thin film is known to have an influence on the magnetic interaction. But, it is noticed that according to the common consensus of APBs alone cannot explain the origin of EB. If majority of APBs end up with mainly anti-ferromagnetic interactions across these boundaries together with the internal ordering modification in Fe3O4, then EB can emerge at low temperatures. Hence, we propose the idea of directional anti-ferromagnetic APB induced EB in Fe3O4 triggered by internal ordering for T <= 200 K. Similar arguments are extended to (111) oriented as well as polycrystalline Fe3O4 films where the grain boundaries can impart same consequence as that of APBs. (C) 2015 Author(s).

Production and recognition bias of stylistic sentences using a story reading task.

Four experiments examined participants' ability to produce surface characteristics of sentences using an on-line story reading task. Participants read a series of stories in which either all, or the majority of sentences were written in the same "style," or surface form. Twice per story, participants were asked to fill in a blank consistent with the story. For sentences that contained three stylistic regularities, participants imitated either all three characteristics (Experiment 2) or two of the three characteristics (Experiment 1), depending on the proportion of in-style sentences. Participants demonstrated a recognition bias for the read style in an unannounced recognition task. When participants read stories in which the two styles were the dative/double object alternation, participants demonstrated a syntactic priming effect in the cloze task, but no consistent recognition bias in a later recognition test (Experiments 3 and 4).

Monetary Policy by Committee:Consensus, Chairman Dominance or Simple Majority?

This paper studies the theoretical and empirical implications of monetary policy making by committee under three different voting protocols. The protocols are a consensus model, where super-majority is required for a policy change; an agenda-setting model, where the chairman controls the agenda; and a simple majority model, where policy is determined by the median member. These protocols give preeminence to different aspects of the actual decision making process and capture the observed heterogeneity in formal procedures across central banks. The models are estimated by Maximum Likehood using interest rate decisions by the committees of five central banks, namely the Bank of Canada, the Bank of England, the European Central Bank, the Swedish Riksbank, and the U.S. Federal Reserve. For all central banks, results indicate that the consensus model is statically superior to the alternative models. This suggests that despite institutionnal differences, committees share unwritten rules and informal procedures that deliver observationally equivalent policy decisions.

Reducing performance bias for unbalanced text mining

In text categorization applications, class imbalance, which refers to an uneven data distribution where one class is represented by far more less instances than the others, is a commonly encountered problem. In such a situation, conventional classifiers tend to have a strong performance bias, which results in high accuracy rate on the majority class but very low rate on the minorities. An extreme strategy for unbalanced, learning is to discard the majority instances and apply one-class classification to the minority class. However, this could easily cause another type of bias, which increases the accuracy rate on minorities by sacrificing the majorities. This paper aims to investigate approaches that reduce these two types of performance bias and improve the reliability of discovered classification rules. Experimental results show that the inexact field learning method and parameter optimized one-class classifiers achieve more balanced performance than the standard approaches.

Improving reliability of unbalanced text mining by reducing performance bias

Class imbalance in textual data is one important factor that affects the reliability of text mining. For imbalanced textual data, conventional classifiers tend to have a strong performance bias, which results in high accuracy rate on the majority class but very low rate on the minorities. An extreme strategy for unbalanced learning is to discard the majority instances and apply one-class classification to the minority class. However, this could easily cause another type of bias, which increases the accuracy rate on minorities by sacrificing the majorities. This chapter aims to investigate approaches that reduce these two types of performance bias and improve the reliability of discovered classification rules. Experimental results show that the inexact field learning method and parameter optimized one class classifiers achieve more balanced performance than the standard approaches.

Effects of study precision and risk of bias in networks of interventions: a network meta-epidemiological study

BACKGROUND Empirical research has illustrated an association between study size and relative treatment effects, but conclusions have been inconsistent about the association of study size with the risk of bias items. Small studies give generally imprecisely estimated treatment effects, and study variance can serve as a surrogate for study size. METHODS We conducted a network meta-epidemiological study analyzing 32 networks including 613 randomized controlled trials, and used Bayesian network meta-analysis and meta-regression models to evaluate the impact of trial characteristics and study variance on the results of network meta-analysis. We examined changes in relative effects and between-studies variation in network meta-regression models as a function of the variance of the observed effect size and indicators for the adequacy of each risk of bias item. Adjustment was performed both within and across networks, allowing for between-networks variability. RESULTS Imprecise studies with large variances tended to exaggerate the effects of the active or new intervention in the majority of networks, with a ratio of odds ratios of 1.83 (95% CI: 1.09,3.32). Inappropriate or unclear conduct of random sequence generation and allocation concealment, as well as lack of blinding of patients and outcome assessors, did not materially impact on the summary results. Imprecise studies also appeared to be more prone to inadequate conduct. CONCLUSIONS Compared to more precise studies, studies with large variance may give substantially different answers that alter the results of network meta-analyses for dichotomous outcomes.

Majority versus minority influence: When, not whether, source status instigates heuristic or systematic processing

Two experiments investigated the extent of message processing of a persuasive communication proposed by either a numerical majority or minority. Both experiments crossed source status (majority versus minority) with message quality (strong versus weak arguments) to determine which source condition is associated with systematic processing. The first experiment showed a reliable difference between strong and weak messages, indicating systematic processing had occurred, for a minority irrespective of message direction (pro- versus counter-attitudinal), but not for a majority. The second experiment showed that message outcome moderates when a majority or a minority leads to systematic processing. When the message argued for a negative personal outcome, there was systematic processing only for the majority source; but when the message did not argue for a negative personal outcome, there was systematic processing only for the minority source. Thus one key moderator of whether a majority or minority source leads to message processing is whether the topic induces defensive processing motivated by self-interest. Copyright (C) 2002 John Wiley Sons, Ltd.

Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).

Error, Bias, and Long-Branch Attraction in Data for Two Chloroplast Photosystem Genes in Seed Plants

Sequences of two chloroplast photosystem genes, psaA and psbB, together comprising about 3,500 bp, were obtained for all five major groups of extant seed plants and several outgroups among other vascular plants. Strongly supported, but significantly conflicting, phylogenetic signals were obtained in parsimony analyses from partitions of the data into first and second codon positions versus third positions. In the former, both genes agreed on a monophyletic gymnosperms, with Gnetales closely related to certain conifers. In the latter, Gnetales are inferred to be the sister group of all other seed plants, with gymnosperms paraphyletic. None of the data supported the modern ‘‘anthophyte hypothesis,’’ which places Gnetales as the sister group of flowering plants. A series of simulation studies were undertaken to examine the error rate for parsimony inference. Three kinds of errors were examined: random error, systematic bias (both properties of finite data sets), and statistical inconsistency owing to long-branch attraction (an asymptotic property). Parsimony reconstructions were extremely biased for third-position data for psbB. Regardless of the true underlying tree, a tree in which Gnetales are sister to all other seed plants was likely to be reconstructed for these data. None of the combinations of genes or partitions permits the anthophyte tree to be reconstructed with high probability. Simulations of progressively larger data sets indicate the existence of long-branch attraction (statistical inconsistency) for third-position psbB data if either the anthophyte tree or the gymnosperm tree is correct. This is also true for the anthophyte tree using either psaA third positions or psbB first and second positions. A factor contributing to bias and inconsistency is extremely short branches at the base of the seed plant radiation, coupled with extremely high rates in Gnetales and nonseed plant outgroups. M. J. Sanderson,* M. F. Wojciechowski,*† J.-M. Hu,* T. Sher Khan,* and S. G. Brady