Information-geometric Markov Chain Monte Carlo methods using Diffusions

Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond Statistics. A full exposition of Markov chains and their use in Monte Carlo simulation for Statistical inference and molecular dynamics is provided, with particular emphasis on methods based on Langevin diffusions. After this geometric concepts in Markov chain Monte Carlo are introduced. A full derivation of the Langevin diffusion on a Riemannian manifold is given, together with a discussion of appropriate Riemannian metric choice for different problems. A survey of applications is provided, and some open questions are discussed.Comment: 22 pages, 2 figure

Including Pervasive Skills in an Accounting Curriculum at a Rural South African University

Accounting programs at South African universities strive to attain and maintain accreditation with the South African Institute of Chartered Accountants (SAICA), an important component of which is incorporating pervasive skills into the curriculum. This paper details how a methodology was identified and adopted in order to incorporate these requirements across the four years of a yet to be accredited professional undergraduate accounting degree. The process commenced by mapping program objectives to individual modules thus facilitating a mapping and scaffolding process of the program. Focus group interviews with discipline leaders resulted in a coherent and coordinated approach to curriculum review which included consideration of the specific needs of students attending a rurally based South African University. The concept of a capstone course was integrated into the final year of the program in order to compliment and complete concepts encountered earlier. Future studies subsequent to the adoption of this methodology may develop or evaluate its efficacy

The geometric foundations of Hamiltonian Monte Carlo

Although Hamiltonian Monte Carlo has proven an empirical success, the lack of a rigorous theoretical understanding of the algorithm has in many ways impeded both principled developments of the method and use of the algorithm in practice. In this paper we develop the formal foundations of the algorithm through the construction of measures on smooth manifolds, and demonstrate how the theory naturally identifies efficient implementations and motivates promising generalizations

Extending the aridity record of the Southwest Kalahari: current problems and future perspectives

An extensive luminescence-based chronological framework has allowed the reconstruction of expansions and contractions of the Kalahari Desert over the last 50 ka. However, this chronology is largely based on near-surface pits and sediment exposures. These are the points on the landscape most prone to reactivation and resetting of the luminescence dating ‘clock’. This is proving to be a limiting feature for extending palaeoenvironmental reconstructions further back in time. One way to obviate this is to sample desert marginal areas that only become active during significant arid phases. An alternative is to find and sample deep stratigraphic exposures. The Mamatwan manganese mine at Hotazel in the SW Kalahari meets both these criteria. Luminescence dating of this site shows the upper sedimentary unit to span at least the last 60 ka with tentative age estimates from underlying cemented aeolian units dating back to the last interglacial and beyond. Results from Mamatwan are comparable to new and previously published data from linear dunes in the SW Kalahari but extend back much further. Analysis of the entire data set of luminescence ages for the SW Kalahari brings out important inferences that suggest that different aeolian forms (1) have been active over different time scales in the past, (2) have different sensitivities to environmental changes and (3) have different time scales over which they record and preserve the palaeoenvironmental record. This implies that future optically stimulated luminescence work and palaeoenvironmental reconstructions must consider both site location and its relationship to desert margins and sediment depositional styles, so that the resolution and duration of the aridity record can be optimally understood

All click, no action?:Online action, efficacy perceptions, and prior experience combine to affect future collective action

Social media is increasingly used for social protest, but does internet-enabled action lead to ‘slacktivism’ or promote increased activism? We show that the answer to this question depends on prior level of activism, and on beliefs about the effectiveness of individual contribution to the collective campaign. Internet-enabled action was varied quasi-experimentally, with participants (n = 143) choosing whether or not to share a campaign on social media. Participants were then informed that sharing on social media had a big (high action efficacy) or small (low action efficacy) impact on achieving the campaign's goal. Prior levels of activism were measured before the experiment, and general levels of collective action were measured one week after the experiment. Taking internet-enabled action for one campaign increased future activism for other campaigns – but only in individuals who were already active and who perceived their actions to be an effective contribution to the campaign

How Crowd Worker Factors Influence Subjective Annotations: A Study of Tagging Misogynistic Hate Speech in Tweets

Crowdsourced annotation is vital to both collecting labelled data to train and test automated content moderation systems and to support human-in-the-loop review of system decisions. However, annotation tasks such as judging hate speech are subjective and thus highly sensitive to biases stemming from annotator beliefs, characteristics and demographics. We conduct two crowdsourcing studies on Mechanical Turk to examine annotator bias in labelling sexist and misogynistic hate speech. Results from 109 annotators show that annotator political inclination, moral integrity, personality traits, and sexist attitudes significantly impact annotation accuracy and the tendency to tag content as hate speech. In addition, semi-structured interviews with nine crowd workers provide further insights regarding the influence of subjectivity on annotations. In exploring how workers interpret a task - shaped by complex negotiations between platform structures, task instructions, subjective motivations, and external contextual factors - we see annotations not only impacted by worker factors but also simultaneously shaped by the structures under which they labour.Comment: Accepted to the 11th AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2023