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Projects 2 and 3 We are developing an information source-set robustness and statistical reliability measure or index for applications in political psychology and political philosophy. The specific context for application is Sino-Western relations, anti-China propaganda, and anti-China sentiement. We are designing two naturalistic studies as pilots, to be further developed into larger naturalistic studies, or else quasi-experiments or full experiments. The pilots and a meta-analysis of similar studies will be used to ascertain required sample sizes to achieve statistical power of 80% with meaningful minimum effect sizes (dependent on test statistics chosen.). Abstract 2 (Draft) : The first experiment is intended to test how much knowledge of the upstream information sources and information source sets of Li-Meng Yan’s COVID-19 article, and of the pre-reviews of that article, inform the public’s reception of the article and their subsequent level of anti-China sentiment. The specific statistical models to be deployed are yet to be determined, and will depend upon initial pilots and meta-analyses used to determine minimum sample sizes and appropriate independent, or predictor, variables.

4 (Draft) : We want to measure sensitivity of different personality types to memetic threat narratives, or threat memes, with additional categories for political alignment and ideo-cultural disposition. Specifically of interest is the propensity to perceive symbolic and physical threat from out groups based upon narratives about those groups, plus memetic replicators possessed by participants. The objective is to determine the extent to which different personality types, when factorially combined with political alignment, religious disposition, and ideology, are prone to feel a sense of symbolic threat, and when they are prone to experience physical threat.

Research Question: Do individual actors get a relatively larger benefit from social media tools compared to group actors and large institutional actors, and what are the interdependencies and interactions involved? Abstract (Draft): We are interested in the hypothesis that social media systems like Twitter are informational force multipliers for interpersonal and social conflict. We further hypothesise that there is a significant damping or mitigating effect for this outcome for large groups and institutions versus motivated individuals. In other words, we hypothesise that the net increase in informational power for an individual is far greater relative to their effort than it is for a group actor or agent. Moreover that, dependent upon certain actor-intrinsic factors, for an individual actor the benefit is sustained for longer or has greater scope/extent relative to effort applied or energy put into the social media network as a communication and information broadcast system. The degree to which this outcome (dependent variable) occurs and is sustained is likely dependent on a set of other significant factors including, but not limited to actor intelligence, actor emotional intelligence, actor education level, actor technological capability and competence, and the access to technology and network infrastructure that is available to the individual informational agent/actor. Definitions (Draft): Informational Force: The ability of any particular item, or else quantity, of information (including semantic information), quantified using any formal method (including Shannon’s theory, infonic situation theory, control systems theory, and general systems theory) to effect change in a system to which it is causally input (via transmission and signalling, for example). Pre-theoretically: IF = (quantity of information) x (net change in system dynamics and behaviour). There is a qualitative variant that takes into account the relative potency of discrete items of information. Two different infons (items of information) might have the same quantitative measure of, say, Shannon entropy, but not have equivalent effects in terms of change on the dynamics of a given system. QIF = Qx(quantity of information) x (net change in system dynamics and behaviour). Where Q is the qualitative and contextual potency co-efficient. Informational Actor/Agent: An individual or group that uses information to effect changes in a system. The system in question could be any human system – including, but not limited to, environmental and ecological systems, the human body and other biological systems, political systems, social systems, administrative and government systems, communication systems, command and control systems, and almost any kind of communication system. In other words, any complex causal system with complex dynamics, processes, and structure, including stochastic and non-linear dynamics. Informational Force Multiplier: Any device, tool, system, or process that multiplies the effect of the energy and informational force input by an agent or other process or system. Method (Draft): A suite of factorial ANOVA and/or regression analysis full experiments. An additional naturalistic study involving the mining of social media data is likely to be necessary for increasing the overall power of the experiment suite and to provide further insight into interactions between independent variables.

3 (Draft) : The second study design is test how much knowledge of the various kinds of upstream information sources (ranked according to reliability) about Xinjiang and Uyghurs influences the degree of anti-China sentiment (dependent variable), of members of the public and policy makers in the West. Participants will be asked to complete an initial survey indicating reliable they think sources are (Likert Scale) and why. Method (Draft): The pilot is likely to be developed using Prolific Academic or MTurk. The full experiment may also involve an analysis of social media output from Twitter and other websites on belonging to media, government, and research bodies and institutes. Independent or predictor variables are likely to include: - Degree and type of exposure to information and pseudo-information source sets from media and social media sources. - Degree and type of exposure to information and pseudo-information from sources like ASPI, Australia’s DFAT, and The US Department of State on line media - Degree and type of exposure to information and pseudo-information from Chinese government affiliated or marked on line sources. - Objective reliability rankings of all information sources based upon a formal ranking scale being developed by SWRG sing information theoretic precepts and principles (this will include a formal, or standardised, classification of sources versus pseudo-information sources). The specific statistical models to be deployed are yet to be determined, and will depend upon initial pilots and meta-analyses used to determine minimum sample sizes and appropriate independent, or predictor, variables. They are likely to involve ANOVA, ANCOVA, and/or regressions analysis. There may be a temporal sequence or within-participants component for before and after exposure to sources like ASPI, Australia’s DFAT, and The US Department of State on line media. Anti-China and pro-China sentiment will be measured using standardised sentiment surveys and scoring systems.

(Draft): We are interested in the effect of religious belief, epistemic beliefs, and psychological profile on levels of Western anti-China sentiment. Method (Draft): Data will initially be sourced from surveys of social media output, but may ultimately involve mixed methods quantitative and qualitative surveys through an on line service such as Amazon's Mechanical Turk. Planned experiments include a factorial ANOVA (experiment 1) and factorial ANCOVA (Experiment 2). Experiment 2 may involve other covariates such as SES, age, political orientation, and education level.

The objective of this thesis is to present a naturalised metaphysics of information, or to naturalise information, by way of deploying a scientific metaphysics according to which contingency is privileged and a-priori conceptual analysis is excluded (or at least greatly diminished) in favour of contingent and defeasible metaphysics. The ontology of information is established according to the premises and mandate of the scientific metaphysics by inference to the best explanation, and in accordance with the idea that the primacy of physics constraint accommodates defeasibility of theorising in physics. This metametaphysical approach is used to establish a field ontology as a basis for an informational structural realism. This is in turn, in combination with information theory and specifically mathematical and algorithmic theories of information, becomes the foundation of what will be called a source ontology, according to which the world is the totality of information sources. Information sources are to be understood as causally induced configurations of structure that are, or else reduce to and/or supervene upon, bounded (including distributed and non-contiguous) regions of the heterogeneous quantum field (all quantum fields combined) and fluctuating vacuum, all in accordance with the above-mentioned quantum field-ontic informational structural realism (FOSIR.) Arguments are presented for realism, physicalism, and reductionism about information on the basis of the stated contingent scientific metaphysics. In terms of philosophical argumentation, realism about information is argued for primarily by way of an indispensability argument that defers to the practice of scientists and regards concepts of information as just as indispensable in their theories as contingent representations of structure. Physicalism and reductionism about information are adduced by way of the identity thesis that identifies the substance of the structure of ontic structural realism as identical to selections of structure existing in re to combined heterogeneous quantum fields, and to the total heterogeneous quantum field comprised of all such fields. Adjunctly, an informational statement of physicalism is arrived at, and a theory of semantic information is proposed, according to which information is intrinsically semantic and alethically neutral.