Political Obligation and Lockean Contract Theory

In John Locke’s Second Treatise of Government, he presents his notion of social contract theory: individuals come together, leave the state of perfect freedom, and consent to give up certain rights to the State so the State can protect its members. He grounds duties and obligations to the government on the basis of consent. Because one consents to the State, either tacitly or expressly, one has consented to taking on political obligations owed to the State. Locke also notes that individuals can withdraw consent and leave the State. This paper challenges the view that political obligation can exist under Locke’s social contract theory. This paper first provides background for the argument by explaining Locke’s position. Then, it examines what consent actually is, ultimately coming to the conclusion that tacit and hypothetical consent are not true forms of consent and cannot justify political obligation, leaving only express consent. Finally, using Isaiah Berlin’s notions of coercion and positive and negative freedoms, this paper looks at whether the current political system allows one to exit the State, leading to the conclusion that if individuals are coerced into consenting to the State, that consent cannot justify political obligation

The Archives Unleashed Project: Technology, Process, and Community to Improve Scholarly Access to Web Archives

The Archives Unleashed project aims to improve scholarly access to web archives through a multi-pronged strategy involving tool creation, process modeling, and community building -- all proceeding concurrently in mutually --reinforcing efforts. As we near the end of our initially-conceived three-year project, we report on our progress and share lessons learned along the way. The main contribution articulated in this paper is a process model that decomposes scholarly inquiries into four main activities: filter, extract, aggregate, and visualize. Based on the insight that these activities can be disaggregated across time, space, and tools, it is possible to generate "derivative products", using our Archives Unleashed Toolkit, that serve as useful starting points for scholarly inquiry. Scholars can download these products from the Archives Unleashed Cloud and manipulate them just like any other dataset, thus providing access to web archives without requiring any specialized knowledge. Over the past few years, our platform has processed over a thousand different collections from over two hundred users, totaling around 300 terabytes of web archives.This research was supported by the Andrew W. Mellon Foundation, the Social Sciences and Humanities Research Council of Canada, as well as Start Smart Labs, Compute Canada, the University of Waterloo, and York University. We’d like to thank Jeremy Wiebe, Ryan Deschamps, and Gursimran Singh for their contributions

A Systematic Review: Effects of Breastfeeding on Early and Late Childhood

Abstract The topic of the long-term impact of breast milk and formula milk composition on the health status of children continues to be a focus of discussion and research. The aim of this systematic review is to describe and critically appraise current evidence regarding the lasting effects of breastfeeding on health outcomes in children throughout early and late childhood. Twenty-one studies focusing on infant feeding were identified using PubMed, CINAHL, and Medline databases. These studies were then categorized according to health outcomes such as: weight, developmental, and immune system effects. Through a critical appraisal of this evidence, it was found that children who were breastfed had improved outcomes compared to those who were formula fed. From these results, recommendations were made in regards to nurses promoting breastfeeding within the clinical setting, which will be further discussed within the systematic review

Content-Based Exploration of Archival Images Using Neural Networks

We present DAIRE (Deep Archival Image Retrieval Engine), an image exploration tool based on latent representations derived from neural networks, which allows scholars to "query" using an image of interest to rapidly find related images within a web archive. This work represents one part of our broader effort to move away from text-centric analyses of web archives and scholarly tools that are direct reflections of methods for accessing the live web. This short piece describes the implementation of our system and a case study on a subset of the GeoCities web archive.This research was supported in part by the Andrew W. Mellon Foundation and the Social Sciences and Humanities Research Council of Canada

Building Community and Tools for Analyzing Web Archives through Datathons

Starting in March 2016, the Archives Unleashed team and our collaborators have brought together social scientists, humanists, archivists, librarians, computer scientists, and other stakeholders to explore web archives as research objects. Three objectives motivated our team to develop and organize these events: facilitating scholarly access, community building, and skills training. We believe that we have been successful on all three fronts. For each event, over the course of two to three days, participants formed interdisciplinary teams and explored web archives using a variety of methods and tools. This paper details our experiences in designing these "datathons", with an intent to share lessons learned, highlight interdisciplinary approaches to research and education on web archives, and describe future opportunities.This research was supported by the Andrew W. Mellon Foundation, the Social Sciences and Humanities Research Council, the National Science Foundation (Grants #1624067, #1723430), Start Smart Labs, Rutgers University, Compute Canada, University of Waterloo, and York University. Additional support came from University of Toronto Libraries, Library of Congress, Internet Archive, British Library, the International Internet Preservation Consortium, Simon Fraser University Libraries, SFU Key, and Université du Québec en Outaouais

Building Community at Distance: A Datathon during COVID-19

This paper aims to use the experience of an in-person event that was forced to go virtual in the wake of COVID-19 as an entryway into a discussion on the broader implications around transitioning events online. It gives both practical recommendation to event organizers as well as broader reflections on the role of digital libraries during the COVID-19 pandemic and beyond.This work is supported by a generous grant from The Andrew W. Mellon Foundation Scholarly Communications program. Additional support was forthcoming from Compute Canada. Authors sincerest thanks to their funders for their support

Tumor-targeting Salmonella typhimurium A1-R in combination with doxorubicin eradicate soft tissue sarcoma in a patient-derived orthotopic xenograft (PDOX) model.

A patient with high grade undifferentiated pleomorphic soft-tissue sarcoma from a striated muscle was grown orthotopically in the right biceps femoris muscle of mice to establish a patient-derived orthotopic xenograft (PDOX) model. Twenty PDOX mice were divided into 4 groups: G1, control without treatment; G2, Salmonella typhimurium (S. typhimurium)A1-R administered by intratumoral (i.t.) injection once a week for 4 weeks; G3, doxorubicin (DOX) administered by intraperitoneal (i.p.) injection once a week for 4 weeks; G4, S. typhimurium A1-R (i.t.) administered once a week for 2 weeks followed by i.p. doxorubicin once a week for 2 weeks. On day 25 from the initiation of treatment, tumor volume in G2, G3, and G4 was significantly lower than G1. Mice found without gross tumor included one mouse (20%) in G2; one mouse (20%) in G3; and 3 mice (60%) in G4. Body weight loss did not significantly differ between the 3 treated groups or from the untreated control. Histological examination revealed eradication of tumor only in G4 where mice were treated with S. typhimurium A1-R followed by DOX. Our present study indicates future clinical potential of combining S. typhimurium A1-R with chemotherapy such as DOX for soft tissue sarcoma patients

The Archives Unleashed Notebook: Madlibs for Jumpstarting Scholarly Exploration

This paper introduces the Archives Unleashed Notebook, which is designed to work with derivative datasets from the Archives Unleashed Cloud, a platform for analyzing web archives. These datasets contain common starting points for scholarly inquiry, including full text content and the domain-level webgraph. Our notebooks interactively walk a scholar through the process of interrogating a collection using a fill-in-the-blanks 'madlibs' approach to promote engagement. Scholars start with a notebook populated with common analyses, in which they can make minor changes to variables to alter the subject of study in systematic ways.This work was primarily supported by the Andrew W. Mellon Foundation. The Social Sciences and Humanities Research Council of Canada provided additional support

The Cost of a WARC: Analyzing Web Archives in the Cloud

The value of web archives to support scholarship in the humanities and social sciences is slowly being realized by the increasing availability of scalable tools and platforms. The cost of providing scholarly access is a critical component of developing a long-term sustainability strategy. This paper attempts to answer a straightforward question: How much does it cost to analyze web archives in the cloud? To make this question more concrete, we examine the creation of three derivatives (extraction of collection statistics, full text, and the webgraph) that serve as the starting points of many scholarly inquiries. Our analysis shows that these typical derivatives costs around US$7 per TB using our Archives Unleashed Toolkit. We describe in detail the methodology and assumptions made to arrive at this figure. To our knowledge, we are the first to quantify the economics of scholarly access to web archives, and we believe that this information is valuable for service planning by archives, libraries, and other institutions.This work was primarily supported by the Andrew W. Mellon Foundation, with additional funding from Start Smart Labs, the Natural Sciences and Engineering Research Council of Canada, the Social Sciences and Humanities Research Council of Canada, and the Ontario Ministry of Research and Innovation's Early Researcher Award program. We'd like to thank our content partners and Raymie Stata for comments on an earlier draft