Autistic Traits and Cognitive Biases for Emotional Faces in Neurotypicals

Total Page:16

File Type:pdf, Size:1020Kb

Autistic Traits and Cognitive Biases for Emotional Faces in Neurotypicals Western University Scholarship@Western Electronic Thesis and Dissertation Repository 10-1-2020 11:00 AM Autistic Traits and Cognitive Biases for Emotional Faces in Neurotypicals Meara Stow, The University of Western Ontario Supervisor: Stevenson, Ryan A., The University of Western Ontario A thesis submitted in partial fulfillment of the equirr ements for the Master of Science degree in Psychology © Meara Stow 2020 Follow this and additional works at: https://ir.lib.uwo.ca/etd Part of the Psychology Commons Recommended Citation Stow, Meara, "Autistic Traits and Cognitive Biases for Emotional Faces in Neurotypicals" (2020). Electronic Thesis and Dissertation Repository. 7451. https://ir.lib.uwo.ca/etd/7451 This Dissertation/Thesis is brought to you for free and open access by Scholarship@Western. It has been accepted for inclusion in Electronic Thesis and Dissertation Repository by an authorized administrator of Scholarship@Western. For more information, please contact [email protected]. Abstract Cognitive biases can involve the tendency to extract some sensory inputs while ignoring others. Cognitive biases impact perception, and subsequent processing decisions made on the basis of perception. Cognitive biases can disrupt accurate and efficient processing of social information, and may underlie core features of social communication difficulties. How cognitive biases contribute to atypical social processing associated with autism spectrum disorder (ASD) traits is unknown. We examined whether cognitive biases for emotional faces were related to scores from the Autism-Spectrum Quotient (AQ), and whether our measures of cognitive biases from a dot- probe paradigm with concurrent eye tracking were comparable. We did not find sufficient evidence to relate ASD traits and cognitive biases. We found limited eye movements made during the paradigm and no relationship between the two concurrent measures. We highlight outstanding questions in the investigation of ASD traits and cognitive biases through the dot- probe paradigm and eye tracking. Keywords Autism Spectrum Disorder, Autistic Traits, Cognitive Bias, Perception, Emotion Processing, Dot-Probe Paradigm, Eye Tracking i Summary for Lay Audience Cognitive biases describe patterns of thinking that affect the decisions people make. We take shortcuts to think quickly about complex problems, and cognitive biases help us to do this. Most biases are stable tendencies that people will continue to display over time, and can affect how we pay attention to, remember, and interpret information. Cognitive biases can look like social and behavioral problems when people deal with information differently, and they may be linked to some of the social and behavioral problems often reported in autism. If there is a link between these two kinds of problems, people with more autism-like features would look at others’ faces differently than people without social and behavioral problems. We largely found people with more autism-like features did not show different cognitive biases when looking at others’ faces, but that factors of our design might have contributed to this being the case. We discuss ways to adapt the current design for future use. ii Acknowledgments I am grateful for the opportunity to express my sincere thanks to my supervisor, Dr. Ryan Stevenson, for his immense patience and encouragement through the completion of this project. I would also like to thank those among my family and friends, the members of the Sensory Perception Lab, and my committee here at Western, whose valuable guidance I will continue to build from. Thank you for tremendous support and for your assistance throughout the completion of this project. iii Table of Contents Abstract ........................................................................................................................................................... i Summary for Lay Audience ...........................................................................................................................ii Acknowledgments ....................................................................................................................................... iii List of Tables ................................................................................................................................................ vi List of Abbreviations ...................................................................................................................................vii List of Figures ............................................................................................................................................ viii List of Appendices ........................................................................................................................................ ix Chapter 1 ........................................................................................................................................................ 1 1 Introduction ........................................................................................................................................... 1 1.1 Cognitive Biases and Social Perception ........................................................................................... 3 1.1.1 Adaptive Mechanisms .................................................................................................................. 4 1.1.2 Evolutionary Mechanisms ............................................................................................................ 5 1.2 Outcomes of Cognitive Biases.......................................................................................................... 6 1.2.1 Biased Perception of Threat ......................................................................................................... 6 1.2.2 Biased Perception of Relevance ................................................................................................... 7 1.2.3 Biased Processing of Experience ................................................................................................. 8 1.2.4 Biased Processing of Rationality.................................................................................................. 8 1.3 Cognitive Biases in Major Clinical Disorders .................................................................................. 9 1.3.1 Cognitive Biases in Neurodevelopmental Disorders ................................................................. 10 1.3.2 Cognitive Biases in Autism Spectrum Disorder (ASD) ............................................................. 11 1.3.3 Cognitive Biases and Autistic Traits .......................................................................................... 15 Chapter 2 ...................................................................................................................................................... 19 2 Indices of Cognitive Biases................................................................................................................. 19 2.1 Tools to Measure Cognitive Biases ................................................................................................ 19 2.1.1 The Dot-Probe Paradigm ............................................................................................................ 19 2.1.2 Beyond the Dot-Probe Paradigm................................................................................................ 21 2.1.3 Eye Tracking .............................................................................................................................. 22 2.2 The Current Study .......................................................................................................................... 25 2.3 The Current Objectives ................................................................................................................... 27 2.4 The Current Design......................................................................................................................... 28 Chapter 3 ...................................................................................................................................................... 31 3 Methods ............................................................................................................................................... 31 3.1 Participants ..................................................................................................................................... 31 iv 3.2 General Procedures ......................................................................................................................... 31 3.3 ASD Traits: The Autism-Spectrum Quotient ................................................................................. 32 3.4 Cognitive Biases in the Eye-Tracked Dot-Probe Paradigm ........................................................... 33 3.4.1 Materials ..................................................................................................................................... 33 3.4.2 Procedures .................................................................................................................................. 34 3.4.3 Data Analyses ............................................................................................................................. 37 3.4.4 Hypotheses ................................................................................................................................
Recommended publications
  • The Evolutionary Roots of Decision Biases: Erasing and Exacerbating Loss Aversion
    Evolution and Loss Aversion 1 Running head: EVOLUTION AND LOSS AVERSION In press, Journal of Personality and Social Psychology Economic Decision Biases in Evolutionary Perspective: How Mating and Self-Protection Motives Alter Loss Aversion Yexin Jessica Li, Douglas T. Kenrick Arizona State University Vladas Griskevicius University of Minnesota Steven L. Neuberg Arizona State University Evolution and Loss Aversion 2 Abstract Much research shows that people are loss-averse, meaning that they weigh losses more heavily than gains. From an evolutionary perspective, loss aversion would be expected to increase or decrease as a function of adaptive context. For example, loss aversion could have helped deal with challenges in the domain of self- protection, but would not have been beneficial for men in the domain of mating. Three experiments examine how loss aversion is influenced by mating and self- protection motives. Findings reveal that mating motives selectively erased loss aversion in men. In contrast, self-protective motives led both men and women to become more loss-averse. Overall, loss aversion appears to be sensitive to evolutionarily-important motives, suggesting that it may be a domain-specific bias operating according to an adaptive logic of recurring threats and opportunities in different evolutionary domains. Key words: Evolutionary psychology, mating, self-protection, decision-biases, loss aversion Evolution and Loss Aversion 3 Economic Decision Biases in Evolutionary Perspective: How Mating and Self-Protection Motives Alter Loss
    [Show full text]
  • Adaptive Bias Correction for Satellite Data in a Numerical Weather Prediction System
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY Q. J. R. Meteorol. Soc. 133: 631–642 (2007) Published online in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/qj.56 Adaptive bias correction for satellite data in a numerical weather prediction system T. Auligne,*´ A. P. McNally and D. P. Dee European Centre for Medium-Range Weather Forecasts, Reading, UK ABSTRACT: Adaptive bias corrections for satellite radiances need to separate the observation bias from the systematic errors in the background in order to prevent the analysis from drifting towards its own climate. The variational bias correction scheme (VarBC) is a particular adaptive scheme that is embedded inside the assimilation system. VarBC is compared with an offline adaptive and a static bias correction scheme. In simulation, the three schemes are exposed to artificial shifts in the observations and the background. The VarBC scheme can be considered as a good compromise between the static and the offline adaptive schemes. It shows some skill in distinguishing between the background-error and the observation biases when other unbiased observations are available to anchor the system. Tests of VarBC in a real numerical weather prediction (NWP) environment show a significant reduction in the misfit with radiosonde observations (especially in the stratosphere) due to NWP model error. The scheme adapts to an instrument error with only minimal disruption to the analysis. In VarBC, the bias is constrained by the fit to observations – such as radiosondes – that are not bias-corrected to the NWP model. In parts of the atmosphere where no radiosonde observations are available, the radiosonde network still imposes an indirect constraint on the system, which can be enhanced by applying a mask to VarBC.
    [Show full text]
  • Boosts in Brain Signal Variability Track Liberal Shifts in Decision Bias
    RESEARCH ADVANCE Boosts in brain signal variability track liberal shifts in decision bias Niels A Kloosterman1,2*, Julian Q Kosciessa1,2, Ulman Lindenberger1,2, Johannes Jacobus Fahrenfort3,4, Douglas D Garrett1,2* 1Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany; 2Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; 3Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; 4Department of Psychology, University of Amsterdam, Amsterdam, Netherlands Abstract Adopting particular decision biases allows organisms to tailor their choices to environmental demands. For example, a liberal response strategy pays off when target detection is crucial, whereas a conservative strategy is optimal for avoiding false alarms. Using conventional time-frequency analysis of human electroencephalographic (EEG) activity, we previously showed that bias setting entails adjustment of evidence accumulation in sensory regions (Kloosterman et al., 2019), but the presumed prefrontal signature of a conservative-to-liberal bias shift has remained elusive. Here, we show that a liberal bias shift is reflected in a more unconstrained neural regime (boosted entropy) in frontal regions that is suited to the detection of unpredictable events. Overall EEG variation, spectral power and event-related potentials could not explain this relationship, highlighting that moment-to-moment neural variability uniquely tracks bias shifts. Neural variability modulation through prefrontal cortex appears instrumental for permitting an organism to adapt its biases to environmental demands. *For correspondence: [email protected] (NAK); [email protected] (DDG) Introduction We often reach decisions not only by objectively weighing different alternatives, but also by allowing Competing interests: The subjective biases to influence our choices.
    [Show full text]
  • The Subtleties of Error Management∗
    The Subtleties of Error Management∗ RYAN MCKAY1,2,3 and CHARLES EFFERSON1,2 1Institute for Empirical Research in Economics, University of Zurich¨ 2Laboratory for Social and Neural Systems, University of Zurich¨ 3Centre for Anthropology and Mind, University of Oxford April 25, 2010 Running title: The Subtleties of Error Management Word count: 6,431 ∗Corresponding author: Ryan McKay, Centre for Anthropology and Mind, University of Ox- ford, 51-53 Banbury Road, Oxford OX2 6PE, United Kingdom [email protected]. 1 Abstract: Error management theory is a theory of considerable scope and emerging influence. The theory claims that cognitive biases do not necessarily reflect flaws in evolutionary design, but that they may be best conceived as design features. Unfor- tunately, existing accounts are vague with respect to the key concept of bias. The result is that it is unclear that the cognitive biases that the theory seeks to defend are not simply a form of behavioral bias, in which case the theory reduces to a version of expected utility theory. We propose some clarifications and refinements of error management theory by emphasizing important distinctions between different forms of behavioral and cognitive bias. We also highlight a key assumption, that the capac- ity for Bayesian beliefs is subject to constraints. This assumption is necessary for what we see as error management theory’s genuinely novel claim: that behavioral tendencies to avoid costly errors can rest on systematic departures from Bayesian beliefs, and that the latter can be adaptive insofar as they generate the former. Key words: error management theory; cognitive biases; behavioral biases; expected utility theory.
    [Show full text]
  • The Evolution of Accuracy and Bias in Social Judgment
    Accuracy and Bias -- 1 The Evolution of Accuracy and Bias in Social Judgment Martie G. Haselton UCLA David C. Funder UC Riverside Chapter in preparation for M. Schaller, J. A. Simpson, & D. T. Kenrick (eds.) Evolution and Social Psychology, Psychology Press. Draft: December 1, 2004 Accuracy and Bias -- 2 The Evolution of Accuracy and Bias in Social Judgment Humans are an intensely social species and therefore it is essential for our interpersonal judgments to be valid enough to help us to avoid enemies, form useful alliances and find suitable mates; flawed judgments can literally be fatal. An evolutionary perspective implies that humans ought to have developed sufficient skills at solving problems of interpersonal judgment, including gauging the personalities of others, to be useful for the basic tasks of survival and reproduction. Yet, the view to be derived from the large and influential bias-and-error literature of social psychology is decidedly different—the social mind seems riddled with fundamental design flaws. We will argue in this paper that flawed design is probably the least plausible explanation for the existence of so many errors. We present an evolutionarily-based taxonomy of known bias effects that distinguishes between biases that are trivial or even artifactual and lead virtually nowhere, and those that have interesting implications and deserve further study. Finally, we present an evolutionary perspective that suggests that the ubiquity, automaticity, and success of interpersonal judgment, among other considerations, presents the possibility of a universal Personality Judgment Instinct. ADAPTATIONS FOR SOCIAL LIFE Archeological evidence and behavioral patterns observed in extant hunter-gatherer groups indicate that the human species has been intensely social for a long time (e.g., Chagnon, 1983, Tooby & Devore, 1987).
    [Show full text]
  • Economic Decision Biases and Fundamental Motivations: How Mating and Self-Protection Alter Loss Aversion
    Journal of Personality and Social Psychology © 2011 American Psychological Association 2012, Vol. 102, No. 3, 550–561 0022-3514/12/$12.00 DOI: 10.1037/a0025844 Economic Decision Biases and Fundamental Motivations: How Mating and Self-Protection Alter Loss Aversion Yexin Jessica Li and Douglas T. Kenrick Vladas Griskevicius Arizona State University University of Minnesota Steven L. Neuberg Arizona State University Much research shows that people are loss averse, meaning that they weigh losses more heavily than gains. Drawing on an evolutionary perspective, we propose that although loss aversion might have been adaptive for solving challenges in the domain of self-protection, this may not be true for men in the domain of mating. Three experiments examine how loss aversion is influenced by mating and self- protection motives. Findings reveal that mating motives selectively erased loss aversion in men. In contrast, self-protective motives led both men and women to become more loss averse. Overall, loss aversion appears to be sensitive to evolutionarily important motives, suggesting that it may be a domain-specific bias operating according to an adaptive logic of recurring threats and opportunities in different evolutionary domains. Keywords: evolutionary psychology, mating, self-protection, decision biases, loss aversion Research at the interface of experimental psychology and eco- are likely to be recurring contexts in which people systematically nomics has demonstrated that psychological factors often lead to weigh gains more than losses. We propose that loss aversion is a seeming irrationalities and limitations in judgment and decision- cognitive bias that would have been well suited to solving certain making processes.
    [Show full text]
  • Over-Representation of Extreme Events in Decision-Making Reflects Rational Use of Cognitive Resources
    Over-representation of extreme events in decision-making reflects rational use of cognitive resources Falk Lieder Helen Wills Neuroscience Institute, University of California, Berkeley Thomas L. Griffiths Department of Psychology, University of California, Berkeley Ming Hsu Haas School of Business, University of California, Berkeley Abstract People’s decisions and judgments are disproportionately swayed by improb- able but extreme eventualities, such as terrorism, that come to mind easily. This article explores whether such availability biases can be reconciled with rational information processing by taking into account the fact that decision- makers value their time and have limited cognitive resources. Our analy- sis suggests that to make optimal use of their finite time decision-makers should over-represent the most important potential consequences relative to less important, put potentially more probable, outcomes. To evaluate this account we derive and test a model we call utility-weighted sampling. Utility-weighted sampling estimates the expected utility of potential actions by simulating their outcomes. Critically, outcomes with more extreme utili- ties have a higher probability of being simulated. We demonstrate that this model can explain not only people’s availability bias in judging the frequency of extreme events but also a wide range of cognitive biases in decisions from experience, decisions from description, and memory recall. Keywords: judgment and decision-making; bounded rationality; cognitive biases; heuristics; probabilistic
    [Show full text]
  • The Subtleties of Error Management∗
    The Subtleties of Error Management∗ RYAN MCKAY1,2,3 and CHARLES EFFERSON1,2 1Institute for Empirical Research in Economics, University of Zurich¨ 2Laboratory for Social and Neural Systems, University of Zurich¨ 3Centre for Anthropology and Mind, University of Oxford April 25, 2010 Running title: The Subtleties of Error Management Word count: 6,431 ∗Corresponding author: Ryan McKay, Centre for Anthropology and Mind, University of Ox- ford, 51-53 Banbury Road, Oxford OX2 6PE, United Kingdom [email protected]. 1 Abstract: Error management theory is a theory of considerable scope and emerging influence. The theory claims that cognitive biases do not necessarily reflect flaws in evolutionary design, but that they may be best conceived as design features. Unfor- tunately, existing accounts are vague with respect to the key concept of bias. The result is that it is unclear that the cognitive biases that the theory seeks to defend are not simply a form of behavioral bias, in which case the theory reduces to a version of expected utility theory. We propose some clarifications and refinements of error management theory by emphasizing important distinctions between different forms of behavioral and cognitive bias. We also highlight a key assumption, that the capac- ity for Bayesian beliefs is subject to constraints. This assumption is necessary for what we see as error management theory’s genuinely novel claim: that behavioral tendencies to avoid costly errors can rest on systematic departures from Bayesian beliefs, and that the latter can be adaptive insofar as they generate the former. Key words: error management theory; cognitive biases; behavioral biases; expected utility theory.
    [Show full text]
  • Qt0mh5z130 Nosplash 60B1ac
    Beyond bounded rationality: Reverse-engineering and enhancing human intelligence By Falk Lieder A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Neuroscience in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Thomas L. Griffiths, Chair Professor Silvia Bunge Professor Friedrich T. Sommer Professor Stuart J. Russell Spring 2018 ©2018 – Falk Lieder all rights reserved. Abstract Beyond bounded rationality: Reverse-engineering and enhancing human intelligence by Falk Lieder Doctor of Philosophy in Neuroscience University of California, Berkeley Professor Thomas L. Griffiths, Chair Bad decisions can have devastating consequences, and there is a vast body of literature suggest- ing that human judgment and decision-making are riddled with numerous systematic violations of the rules of logic, probability theory, and expected utility theory. The discovery of these cogni- tive biases in the 1970s challenged the concept of Homo sapiens as the rational animal and has pro- foundly shaken the foundations of economics and rational models in the cognitive, neural, and so- cial sciences. Four decades later, these disciplines still lack a rigorous theoretical foundation that can account for people’s cognitive biases. Furthermore, designing effective interventions to remedy cog- nitive biases and improve human judgment and decision-making is still an art rather than a science. I address these two fundamental problems in the first and the second part of my thesis respectively. To develop a theoretical framework that can account for cognitive biases, I start from the assump- tion that human cognition is fundamentally constrained by limited time and the human brain’s finite computational resources.
    [Show full text]
  • Is Anchoring on Estimates of Severity an Adaptive Heuristic?
    Georgia Southern University Digital Commons@Georgia Southern Electronic Theses and Dissertations Graduate Studies, Jack N. Averitt College of Spring 2014 Is Anchoring on Estimates of Severity an Adaptive Heuristic? Joy E. Losee Follow this and additional works at: https://digitalcommons.georgiasouthern.edu/etd Part of the Cognitive Psychology Commons, and the Social Psychology Commons Recommended Citation Losee, Joy E., "Is Anchoring on Estimates of Severity an Adaptive Heuristic?" (2014). Electronic Theses and Dissertations. 1117. https://digitalcommons.georgiasouthern.edu/etd/1117 This thesis (open access) is brought to you for free and open access by the Graduate Studies, Jack N. Averitt College of at Digital Commons@Georgia Southern. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of Digital Commons@Georgia Southern. For more information, please contact [email protected]. 1 IS ANCHORING ON FORECASTS OF SEVERE WEATHER AN ADAPTIVE HEURISTIC? by JOY E. LOSEE (Under the Direction of Karen Z. Naufel) ABSTRACT Decisions to either to prepare or not prepare for weather threats involve uncertainty. Uncertainty in decision making often involves the potential for making either a false positive (preparing for a storm that never arrives) or a false negative error (not preparing for a real storm). Error Management Theory (EMT; Haselton & Buss, 2000) posits that, depending on the uncertain context, people select a decision-making strategy that favors one error over the other. Related to weather, research has shown that people prefer a false positive, or an overestimation (Joslyn et al., 2011). Particularly, this overestimation appears when people receive severe information prior to making a judgment.
    [Show full text]
  • Trump's $2 Trillion Mistake, the “War on Energy Efficiency
    ATTACHMENT TRUMP’S $2 TRILLION MISTAKE, THE “WAR ON ENERGY EFFICIENCY: The “command-but-not-control” approach of fuel economy and energy efficiency performance standards delivers consumer pocketbook savings, grows the economy and protects public health Version 1.1 December 1, 2017 TABLE OF CONTENTS EXECUTIVE SUMMARY xiii I. INTRODUCTION 1 The Consumer Stake in Energy Efficiency Standards Foregone Energy Savings and Tax Reform Household Energy Expenditures A Consumer Issue Analyzed from a Consumer Point of View The Origin of Efficiency Standards The Stakes for consumers A Pragmatic Consumer Approach Outline PART I. THE LEGAL FRAMEWORK FOR REGULATING FUEL CONSUMPTION AND EMISSIONS FROM VEHICLES II. THE LEGAL TERRAIN OF STANDARDS FOR FUEL ECONOMY AND 10 ENVIRONMENTAL PROTECTION Laws Governing Agency Action The Complex Terrain of Energy Efficiency Standards Setting Identifying the Range of Options Reconciling the Institutional and Legal Differences of a Complex Economic and Environmental Challenge The Inseverable Link between Energy Consumption and Emission of Pollutants American Federalism at its Best Executive Branch Guidance on Rulemaking The Legal Context of Regulatory Reform of Fuel Economy Standards Executive Orders Physics, Law and Economics Go Hand in Glove in the Rulemaking Process III. THE IMPORTANCE OF RIGOROUS BENEFIT-COST ANALYSIS IN CORRECTING 24 MARKET FAILURES The Foundation of Energy Policy in Market Imperfections Benefits and Costs Market Imperfections Fundamental Economic Perspectives The LBL Investment/Technology Adoption Framework The Welfare Economics of Vigorous Policy Action Conceptual Specifications of Market Imperfections Lawrence Berkeley Laboratory Resources for the Future Other Recent Comprehensive Efficiency Gap Frameworks Conclusion: The Increasing Urgency of Closing the Efficiency Gap i PART II.
    [Show full text]
  • Negative Interpretation Biases Precede the Onset of Psychosis
    Available online at www.sciencedirect.com ScienceDirect Behavior Therapy 50 (2019) 718–731 www.elsevier.com/locate/bt Negative Interpretation Biases Precede the Onset of Psychosis Jenny Yiend King’s College London Paul Allen King’s College London Natalie D. Lopez King’s College London Irina Falkenberg King’s College London Department of Psychiatry & Psychotherapy, Philipps-University Marburg, Germany Huai-Hsuan Tseng King’s College London Philip McGuire King’s College London psychosis, and could therefore contribute to its development. This study investigated whether a negative interpretation Biased interpretation mechanisms could be a new target for bias was present in people at high risk for psychosis. People clinical intervention in the early phase of psychosis. with an At Risk Mental State (ARMS; n = 21), patients with First Episode Psychosis (FEP; n = 20), and healthy controls (n = 20) performed three tasks, each of which was designed Keywords: interpretation bias; psychosis; at-risk mental state; to measure interpretation bias. Both ARMS and FEP cognitive vulnerability participants showed an attenuated positive bias compared to controls. These findings extend previous results investi- COGNITIVE BIASES ARE DEFINED as “the selective gating interpretation bias in psychosis by showing that processing of pathology congruent information that interpretative biases are present before the onset of might confirm a pathological belief” (Savulich, Shergill & Yiend, 2012, p. 516). More specifically, interpretation bias is defined as “a consistent We thank Yuanyuan Huo, Damla Irez and Katie Davis for tendency to interpret emotionally ambiguous stimuli, assistance with data collection; George Savulich for assistance with situations, or events in a negative (or positive) preparation of the tasks and Josie Parkhouse for assistance in ” formatting the manuscript.
    [Show full text]