Textbook Evaluation Toolkit

In Spring 2018, the LaGuardia Community College Library department was awarded a New York State grant to train students to evaluate textbooks. The goal of the project is to give faculty tools to help students evaluate the books being used in their classes. It is not expected that all of these tools will be used in a single class, but rather that faculty will use some of these tools to determine how textbooks are working, and not working, for their students. The seminar introduced students to the economics and politics of the textbook industry and gave them tools to evaluate textbooks. This repository contains the materials used during the seminar

Teaching Students to Critically Evaluate Textbooks

This chapter is a case study describing how library faculty combined service learning and information literacy to help students evaluate textbooks, comparing commercial ones to Open Education Resources. The underlying idea was to give students not only a scholarly grounding that would help them as they move through their academic careers but also a practical vocational orientation to help them succeed in the workforce and, hopefully, become future contributors to the free culture movement

An Analysis of Big Data on Health: Critique is Not Optional

The ‘social’ has always been a commercial and scientific resource – now in the digital age the competition regarding claims to which disciplines have justified understandings of this domain have intensified. The social sciences need to defend their subject area in order to preserve it. An application of the netnographic approach (Kozinets, 2010), social network analysis, data mining and machine-learning tools to highlight the certainties and uncertainties of Big Data and the Health Industry in order to start the process of uncovering the social and cultural forces that they are appropriating. What follows is the application of the tools of Big Data analytics on those that conduct Big Data analytics. There are competing discourses surrounding ‘Big Data’ and Health. On the one hand business, marketing and advertising interests are promoting Big Data as information that no longer requires theory or the scientific methodologies of old. On the other are voices from the academy; digital humanities and computational social sciences that wish to benefit from the volumes of available data. It is these (and other) competing discourses that are the target of this research. This paper argues that those engaged in ‘data without theory’ are generating a relational social mechanism similar to that of self-fulfilling prophesies of Merton, the network effects of Coleman and the bandwagon effects of Granovetter (Donati, 2015:66) and leaving no room for critique

Are there multiple kinds of episodic memory? An fMRI investigation comparing autobiographical and recognition memory tasks

What brain regions underlie retrieval from episodic memory? The bulk of research addressing this question with fMRI has relied upon recognition memory for materials encoded within the laboratory. Another, less dominant tradition has used autobiographical methods, whereby people recall events from their lifetime, often after being cued with words or pictures. The current study addresses how the neural substrates of successful memory retrieval differed as a function of the targeted memory when the experimental parameters were held constant in the two conditions (except for instructions). Human participants studied a set of scenes and then took two types of memory test while undergoing fMRI scanning. In one condition (the picture memory test), participants reported for each scene (32 studied, 64 nonstudied) whether it was recollected from the prior study episode. In a second condition (the life memory test), participants reported for each scene (32 studied, 64 nonstudied) whether it reminded them of a specific event from their preexperimental lifetime. An examination of successful retrieval (yes responses) for recently studied scenes for the two test types revealed pronounced differences; that is, autobiographical retrieval instantiated with the life memory test preferentially activated the default mode network, whereas hits in the picture memory test preferentially engaged the parietal memory network as well as portions of the frontoparietal control network. When experimental cueing parameters are held constant, the neural underpinnings of successful memory retrieval differ when remembering life events and recently learned events

Analysis of milk-borne public health risks in milk markets in Kenya

The major role played by informal milk markets in Kenya and the benefits to those associated with it are now widely acknowledged. The benefits include higher prices for farmers, income generation for the market agents and convenient delivery and lower prices for poor consumers. However, in spite of these benefits, regulations governing informal marketing of milk continue to be unfavourable and do not reflect local realities of milk marketing, having been based on models derived from industrialised countries where virtually all milk destined for the market is pasteurised and packaged. Results of risk assessment, including HACCP analysis, of milk quality and handling practices of informal milk market agents and consumers in central and southern Kenya show variable apparent prevalence of zoonotic health hazards in marketed milk, high bacterial counts especially in outlets associated with longer market chains. Notably, the ineffectiveness of current regulations was reflected in the lack of difference in the quality of milk sold by licensed and non-licensed traders. The study shows that health risks from the bacterial hazards identified are mitigated by the common consumer practice of boiling milk before consumption. The most important health risks were judged to be from two main sources: (i) anti-microbial residues found in up to 15% of milk samples tested and (ii) consumption of naturally fermented milk. Proposals for management of these health risks and the engagement of stakeholders and key players in the process to achieve more favourable policy environment policy are presented and discussed

Parallelized and Vectorized Tracking Using Kalman Filters with CMS Detector Geometry and Events

The High-Luminosity Large Hadron Collider at CERN will be characterized by greater pileup of events and higher occupancy, making the track reconstruction even more computationally demanding. Existing algorithms at the LHC are based on Kalman filter techniques with proven excellent physics performance under a variety of conditions. Starting in 2014, we have been developing Kalman-filter-based methods for track finding and fitting adapted for many-core SIMD processors that are becoming dominant in high-performance systems. This paper summarizes the latest extensions to our software that allow it to run on the realistic CMS-2017 tracker geometry using CMSSW-generated events, including pileup. The reconstructed tracks can be validated against either the CMSSW simulation that generated the hits, or the CMSSW reconstruction of the tracks. In general, the code's computational performance has continued to improve while the above capabilities were being added. We demonstrate that the present Kalman filter implementation is able to reconstruct events with comparable physics performance to CMSSW, while providing generally better computational performance. Further plans for advancing the software are discussed