The brain, self and society: a social-neuroscience model of predictive processing

Kelly, Michael P.; Kriznik, Natasha M.; Kinmonth, Ann Louise; Fletcher, Paul C.

doi:10.1080/17470919.2018.1471003

Cited by 21 publications

(15 citation statements)

References 42 publications

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“…To get the same original outputs despite what Leximancer calls a stochastic process of generating maps (https://info.leximancer.com/tutorial-guides), we learnt that a query needs to run “from scratch.” There seems to be a need for better integration of skills from social science and computer science to understand such “black boxes” of machine learning and algorithms for data and evidence synthesis . There are some intriguing parallels between the way that the software learns from the data and the way that both phenomenology and neuroscience describe the plasticity of human perception—the way that humans learn from the data and information they are exposed to . Alfred Schutz distinguished between ideal types as higher order organizing concepts and lower level more plastic typifications that are used to make sense of everyday life .…”

Section: Discussionmentioning

confidence: 99%

“…13 There are some intriguing parallels between the way that the software learns from the data and the way that both phenomenology and neuroscience describe the plasticity of human perception-the way that humans learn from the data and information they are exposed to. 46 Alfred Schutz distinguished between ideal types as higher order organizing concepts and lower level more plastic typifications that are used to make sense of everyday life. 47,48 Typifications change and evolve as new information becomes available.…”

Section: Future Research and Epistemological Inquirymentioning

confidence: 99%

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Semiautomated text analytics for qualitative data synthesis

Haynes

Garside

Green

et al. 2019

Research Synthesis Methods

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Approaches to synthesizing qualitative data have, to date, largely focused on integrating the findings from published reports. However, developments in text mining software offer the potential for efficient analysis of large pooled primary qualitative datasets. This case study aimed to (a) provide a step‐by‐step guide to using one software application, Leximancer, and (b) interrogate opportunities and limitations of the software for qualitative data synthesis. We applied Leximancer v4.5 to a pool of five qualitative, UK‐based studies on transportation such as walking, cycling, and driving, and displayed the findings of the automated content analysis as intertopic distance maps. Leximancer enabled us to “zoom out” to familiarize ourselves with, and gain a broad perspective of, the pooled data. It indicated which studies clustered around dominant topics such as “people.” The software also enabled us to “zoom in” to narrow the perspective to specific subgroups and lines of enquiry. For example, “people” featured in men's and women's narratives but were talked about differently, with men mentioning “kids” and “old,” whereas women mentioned “things” and “stuff.” The approach provided us with a fresh lens for the initial inductive step in the analysis process and could guide further exploration. The limitations of using Leximancer were the substantial data preparation time involved and the contextual knowledge required from the researcher to turn lines of inquiry into meaningful insights. In summary, Leximancer is a useful tool for contributing to qualitative data synthesis, facilitating comprehensive and transparent data coding but can only inform, not replace, researcher‐led interpretive work.

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Section: Discussionmentioning

confidence: 99%

Section: Future Research and Epistemological Inquirymentioning

confidence: 99%

Semiautomated text analytics for qualitative data synthesis

Haynes

Garside

Green

et al. 2019

Research Synthesis Methods

View full text Add to dashboard Cite

show abstract

“…Social interactions add an additional domain to how we how we interpret or infer our own behaviour, an extra domain for which the brain must account for in its model of the world. The putative computational substrates of how these shared domains are formed or inferred and modulated in the choice blindness paradigm is an area we wish to explore in the future (Bolis & Schilbach, 2020;Kelly, Kriznik, Kinmonth, & Fletcher, 2019;Ramstead, Veissière, & Kirmayer, 2016).…”

Section: Choice-induced Preference Change In Groupsmentioning

confidence: 99%

Choice blindness and choice-induced preference change in groups

Pärnamets¹,

J²,

Raafat³

et al. 2020

Preprint

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Contrary to common belief, our preferences do not only shape our decisions but are also shaped by what decisions we make. This effect, known as choice-induced preference change, has been extensively studied in individuals. Here we document choice-induced preference change in groups. We do so by using the choice-blindness paradigm, a method by which participants are given false feedback about their past choices. Participants are given a second round of choices following the choice blindness manipulation´measuring preference change resulting from accepting the manipulation. In Experiment 1 (N=83), we introduce a roommate selection task used in this paper and use it to replicate choice-induced preference change using choice-blindness in individuals. In Experiment 2 (N=160), dyad members made mutual choices in the roommate selection task and then receive either veridical or false feedback about what choice they made. The majority of the false feedback trials were accepted by the dyads as their own choices, thereby demonstrating choice blindness in dyads for the first time. Dyads exhibited choice-induced preference change and were more likely to choose the originally rejected option on trials where they accepted the manipulation compared to control trials. In Experiment 3 (N=80), we show that the preference effect induced by the choice blindness manipulation at the group level does not generalize back to follow up choices made by individual participants when removed from the group. In all studies, response time analyses further support our conclusions. Choice-induced preference change exists for both individuals and groups, but the level at which the choice was made constrains the influence of that choice on later preferences.

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“…This is their sense of who and what they are, being a unique individual separate from others, and what their place in the world is. 27 However, this sense of self and the sense of self-determination that goes with it are at least partly illusory. This is because some behavior is automatic 28 and because individuals are enmeshed in relationships with others.…”

Section: Evidence Of Behavior Change Interventionsmentioning

confidence: 99%

Is It Justifiable to Make Self-Determination Illusory to Motivate a Specific Health Outcome?

2020

AMA Journal of Ethics

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A nudge is an intervention designed to prompt people to "voluntarily" make the choice intended by those who altered the choice environment or situation, and therefore using nudges is thought to undermine selfdetermination. Evidence for this assumption is weak, however, and sets aside much of what we know about human conduct sociologically. This paper argues that the practical consciousness that people have about their own actions and reasons for executing those actions can inform our thinking about motivating compliance with treatments in clinical settings and the ethical issues involved. Case Mr H is a 58-year-old man with insulin-dependent diabetes, hypertension, and class II obesity (with a BMI of 35 kg/m 2). Mr H sees Dr K today after a 6-month trial of lifestyle changes to lose weight because he wasn't interested in taking anti-obesity medications. As Mr H has told Dr K in the past, "I am already on too many medications for my sugar and blood pressure." Evaluation reveals that Mr H's BMI has increased since the last visit, and Dr K is increasingly concerned, given Mr H's strong family history of coronary artery disease. Recalling that Mr H is afraid of bariatric surgery, Dr K considers reiterating the risk of death and a drawn-out recovery period as Mr H's most feared drawbacks of surgery in order to prompt Mr H to agree to taking anti-obesity medication. 1,2,3

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The brain, self and society: a social-neuroscience model of predictive processing

Cited by 21 publications

References 42 publications

Semiautomated text analytics for qualitative data synthesis

Semiautomated text analytics for qualitative data synthesis

Choice blindness and choice-induced preference change in groups

Is It Justifiable to Make Self-Determination Illusory to Motivate a Specific Health Outcome?

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