2,778 research outputs found
Marcus Joseph Wright memoirs, MSS.1585
No full textAbstract: An incomplete typescript copy (18 pp.) of, "Memoirs of Brigadier General Marcus J. Wright, CSA."Scope and Content Note: The collection contains an incomplete typescript copy (18 pp.) of, "Memoirs of Brigadier General Marcus J. Wright, CSA," which includes a family genealogy, and accounts of his early life in Tennessee and his career.Biographical/Historical Note: Confederate General and author from Tennessee
Marcus on Belief and Belief in the Impossible
No full textI review but don’t endorse Marcus’ arguments that impossible beliefs are impossible. I defend her claim that belief’s objects are, in some important sense, not the bearers of truth and falsity, discuss her dispositionalism about belief, and argue it’s a good fit with the idea that belief’s objects are Russellian states of affairs.
Reviso, pero no suscribo, los argumentos de Marcus a favor de que las creencias imposibles son imposibles.
Defiendo su tesis de que los objetos de las creencias no son, en algún sentido importante, los soportes
de la verdad y la falsedad; discuto su disposicionalismo acerca de las creencias y argumento que encaja bien
con la idea de que los objetos de las creencias son estados de cosas russellianos
Inventory of types of consumer data and data collection methodologies for consumer-generated food consumption data: D7.1
No full textThe overall aim of RICHFIELDS is to design a research infrastructure for the collection, integration, processing and sharing of consumer generated data as related to food behavior and associated lifestyle activities. An important part of the RICHFIELDS design will center on the evaluation of the scientific, technical, legal and ethical aspects related to integration and governance of consumer-generated data on food behavior. The tasks related to Deliverables5.1 to 7.1 are to implement the provided quality framework and operationalization of Deliverables 5.3-7.3 and to collect the necessary data for the creation of an inventory of data and data collection tools. The aim of the inventory is to provide a list of data collection tools which is representative for the variety of tools used by and accessible to the general public, the methodologies they implement, the health and lifestyle parameters they collect and integrate. The tools and data collected in this inventory provide the basis for the identification of possible scientific, legal, technical and ethical gaps and needs regarding the use and integration of the consumer generated food behavior data and to capture developments to improve or simplify current practices in the collection and integration of food consumption data. The Deliverables 5.1-7.1 share a common framework and tool for data collection, but the tools and scientific data collected for the inventory are specific for the domains purchase (D5.1), preparation (D6.1) and consumption (D7.1)). Also, domain specific search strategies for the generation of their respective part of the inventory have been applied. The present report is based on the inventory of tools related to food consumption and lifestyle data (Deliverable 7.1). The result of this deliverable are 1) the inventory in the form of a database of food consumption tools and methodologies (mainly smart phone apps) including the associated quality information related to the dimensions of scientific relevance, legal governance and data management, which was collected based on the quality framework and operationalizations developed and described in Deliverable 7.3, 2) a description of the methodology underlying the generation of this inventory including the tool selection and data collection process and 3) aggregations of relevant descriptive data about the tools listed in the inventory. Aggregations, analyses and evaluations of the collected information related to the quality criteria developed in Deliverable 7.3 will be part of Deliverable 7.4 and 7.5
Report on the synthesis of findings for WP5-7 phase 1: D4.2
No full textIn order to support the design of the Research Infrastructure (RI) Phase 1 was tasked with exploring the range of consumer-generated data currently collected, mainly via smart phone applications and tools (APPS) in terms of the type and quality of consumer-generated data collected and consumers’ perspectives on willingness to share their data with researchers. The purpose of this deliverable, is to provide input to the final design of the proposed RICHFIELDS RI by Phase 3 and insight for the development of the wider roadmap proposal for the FNH-RI by synthesising the findings across the three domains within Phase 1 (purchase, preparation and consumption); highlighting opportunities and potential limitations for the scientific use of consumer-generated data; identifying potential opportunities/issues that are relevant for the final design of the RICHFIELDS RI/data platform (Phase 3), but which may not be covered specifically in the Phase 1 deliverables
Inventory of types of consumer-generated food preparation data and data collection methodologies: D6.1
No full textThe RICHFIELDS project aims to design a Research Infrastructure (RICHFIELDS RI) for the collection, integration, processing and sharing of consumer-generated data as it relates to food behaviour and lifestyle determinants. In order to achieve this, it is necessary to explore the range of consumer-generated data currently available, in terms of its type and quality.This document reports a scoping exercise to examine the breadth of domestic food preparation apps currently available in the marketplace that collect consumer-generated data related to food preparation and create an inventory of prototypical examples of these applications. It additionally aimed to test the feasibility of applying the Quality Criteria set outin Deliverable 6.3 for the classification of apps, and other related ICT, namely descriptive, scientific, legal and technical characteristics. To this end, a search was made of UK based retailers of mobile applications, or apps. Apps arising from this search were then classified according to a set definition of domestic food preparation and a typology of available apps was created.This report highlights the breadth of domestic food preparation apps that collect consumergenerated data currently available in the marketplace and the range of data collected by these apps. The search protocol identified a multitude of available apps. These search results were narrowed to a final list of 54 prototypical apps that represent those available in the current marketplace. These prototypical apps can be said to fulfil three main user motivations. That is, to gain ‘knowledge and understanding’, gain assistance with ‘meal preparation and cooking’, and the ‘planning and organisation’ of meals, foods and meal plans. Within the category of ‘knowledge and understanding’, the primary user behaviour was that of ‘searching for information’ and/or the ‘sharing of knowledge and experience’ with others. Many domestic food preparation apps – such as a recipe database app (e.g., Paprika Recipe manager) - provide the consumer with the ability to search for information by either within pre-determined categories (e.g., breakfast, lunch, dinner) or by entering a search term. A common feature of this category of apps is also to allow the consumer with the ability to share information with others, such as by posting to social media or emailing the information to another. The feasibility for the application of the quality criteria set out in Deliverable 6.3 was tested, and in many cases, the level of detail necessary to fulfil these criteria was not publically available. In many cases, the specificity of these quality criteria did not afford the flexibility necessary for the sufficient categorisation of these apps according to these criteria. It is recommended that these quality criteria are reviewed in line with the finding of this exercise and the classification of consumer-generated data at an app level be reconsidered.Legal and technical quality criteria fields were completed for apps where information was available. However, as stated above this information was not publically available in all cases. This raises an interesting ethical issue as regards the inclusion of apps and/or data into the RICHFIELDS RI where consumers do not have ready access to the terms and conditions of use. When the information was publically available, the terms and conditions were often difficult to interpret by researchers without a legal and technical background
Report on gaps and needs - WP6: report on the potentials and limitations for the use of user-generated domestic food preparation data to answer questions regarding determinants of nutrition and eating: D6.5
No full textThe overarching aim of RICHFIELD’s Phase 1 is to explore the available consumer-related data on food purchase, preparation and consumption, in terms of its type and quality. This Phase consists of three Workpackages(WP5-7) which study food purchase (WP5), preparation (WP6) and consumption (WP7). This report aims to identify the potential and limitation of present and future data to answer key question on the determinants of domestic food preparation. An inventory of types of domestic food preparation data and data collection methodologies was conducted. A scoping exercise was performed with the aim of identifying the range of available domestic food preparation applications (apps) that collected user-generated data. The results of this exercise were evaluated and from this, 54 prototypical examples of domestic food preparation apps were identified and classified. For 48 (89%) of the apps, the motivation for use was classified as ‘Knowledge and Understanding’ with 33 (61%) allowing the user to ‘Search for information’, and 15 (28%) for the user to ‘Share knowledge and experience’. A further 53 (98%) were classified as having the ‘Planning and organisation’ as their primary motivation for use, of these 18 (33%) allowed the user to perform ‘Recipe management’, ten (18%), to perform ‘Meal/menu planning’ and 25 (46%) to carry out ‘Documenting/recording of food’. A further 18 (33%) apps fell into the category of ‘Meal preparation and cooking’, within this classification, nine (17%) apps were classified as ‘Interacting with sensors’, and nine (17%) apps ‘classified as using apps as cooking aids.’Users’ primary motivation for using domestic food preparation apps is to develop personal food knowledge, skills and/or abilities. This opens up the potential to answer research questions relating to Individual Psychological determinants, such as food beliefs, habits and self-regulation in relation to food. However, the limited availability of contextual data, such as that at the ‘Individual/Situation’, and ‘Interpersonal/Social’ levels, means that much of this data is detached from the user. Researchers intending to use this data will have to carefully consider the degree to which additional contextual information is required to draw conclusions. The interconnectedness of the apps presents new opportunities to further enrich the collected data from external sources. There is the potential to create ‘links’ between multiple app usages from a single user. For example, it may be useful to gain domestic food preparation specific information from dedicated apps, and enrich this with demographic, situational and social context data collected through apps such as Facebook, Twitter and Instagram. However, the degree to which users would find this interlinkage acceptable still needs to be investigated. A further point to consider with user-generated domestic food preparation data, is the degree to which it can act as a ‘proxy’ for intake. The data collected via app usage reflects the motivation to gain knowledge and to develop skills. The degree to which this is translated into intake cannot be directly drawn from the data in its current form. At best, it describes an ‘intention’ to intake certain foods and/or meals. Again, it is possible to link data from the consumption apps identified in WP7 and map food choice and eating behaviour from preparation through to consumption. Although, a protocol for performing such exercises still needs to be developed. Finally, the availability and accessibility of the user-generated data for use in the RICHFIELDS RI still needs to be established. It is essential that legal and technical experts work with the RI to ensure easy and cost effective access to multiple big-data sets for the RICHFIELD end user
Development of a quality evaluation framework for consumer generated domestic food preparation data: D6.3
No full textThis deliverable formulates a set of quality criteria for the evaluation of this consumergenerated food preparation data in terms of its scientific relevance and technical and legal governance. These three area were selected as indicators of quality as they allow for the assessment of data in relation to key questions relating to domestic food preparation behaviour (i.e., What/Who/Why/How and Where). This is, in addition to assessing the legal limitations, organizational restrictions, confidentiality and privacy concerns related to collection, integration and dissemination of consumer-generated data and the technical protocols and standards for data access and data processing. Information about these topics is crucial for developing the blueprint of a data platform, such as RICHFIELDS, as well as for its data governance structure.In addition to providing a framework for the evaluation of data quality, the result of this deliverable also provides structure and guidance for the data collection process of deliverable 6.1, which is an inventory of consumer-generated food preparation data tools. Morespecifically, this quality framework provides an operationalised definition for each quality criteria in the form of a set of relevant questions that should be answered for each tool included in the RICHFIELDS Inventory Management System (RIMS). RIMS is an online management system for the storage and assessment of tools that produce consumergenerated data on the purchase, preparation, consumption of food and/or beverages and their associated lifestyle data that could potentially be of use to social science researchers.RIMS comprises two component parts; [1] a typology of the tools stored within the inventory, and [2] a list of quality criteria against which each tool can be evaluated. The typology is a scheduled framework categorizing the food preparation tools according to defined groupings. The current typology for food preparation is a four-level model. The firstlevel is the overall domain - in this instance, domestic food preparation. The second level reflects the goal of underlying motivation of the behaviour captured by the tool. The third level reflects the specific behaviours captured by the tool and the final level is indicative of the recorded behaviour. The identified quality criteria are based on aspects of health and lifestyle specific to food consumption. Preparation behaviours are in some respect quite distinct and different from food intake, as they frequently require a degree of pre-behaviour decision making such as looking up a recipe. In this regard the current quality criteria don’t sufficiently capture ‘intended’ behaviours, only enacted behaviours. The next step for these criteria is to test them with the tools currently in RIMS. However, for these tools it will be challenging to validate them according to current criteria at the level required for the inventory presented in deliverable 6.1. As for many tools, it is not possible to respond to these the criteria, particularly with the feasibility parameters worked to in this exercise. That is to say, it is not possible to easily identify certain aspects of a tool’s quality without either expert knowledge of the fields of ICT and Law, and without the downloading and the downloading and testing of a tool, the examination of a tool’s data structure and/or the examination of a hosting data infrastructure. This is therefore a potentially time consuming and costly process to validate the quality of consumer-generated data produced via a tool
Definition of gaps and needs on quality and availability of data to answer the relevant questions on determinants of food purchase: D5.5
No full textThe aim of deliverable 5.5 was to define gaps and needs and identify potentials and limitations with the tools collected in the WP 5 inventory. The data collection process of the purchase tools were investigated and covered by considering what/who/why/how the toolsmet the food purchase purpose, the method/s used for data collection, contextual influences on the purchase and intentional or actual eating behaviour were also covered in the investigation. The type of data which we found interesting from a RICHFIELDS perspective, potentiallyexplaining consumer purchase behaviour was 1) the purpose of the tool (i.e. the user´s motivation for using the app), 2) the purchase method “how was purchased”, 3) the product characteristics “what unit”, 4) “how much” and 5) possible contextual influences on users’ purchase behaviour. These data have the potential to be used for key research questions (i.e., What/Who/Why/How).Our result shows that the purchase apps in our inventory are a heterogeneous sample of mobile apps supporting the users in different phases of the purchase process. And apps in the same category do not even generate the same kind of data. Generated data can also be intentional purchase data, or actual, or both intentional and actual. This result makes it very difficult to draw any conclusion and characterise a typical app in each of the four categories(i.e. the four purposes). However, an integration of food purchase data with relevant contextual generated data has the potential to give a more reliable picture of consumer purchase and eating behaviour. And moreover, purchase data together with preparation and consumption generated data have a potential to give a more complete picture of consumer behaviour since food activities are complex and is influenced by many factors. Some identified limitations are that the availability of publicly accessible data about the collected tools is limited. There is a lack of documentation about the procedures for data access and insufficient information about the technical infrastructure for data access. The limitations about e.g. the tools´ documentation of options and methods for accessing and extracting data, technical infrastructure for data assess as well as what format the generated data has are connected to large challenges in the continuation of the RICHFIELDS project. The last and final phase [phase 3] of the project aims to design the research infrastructure and its governance, intellectual property rights and ethical aspects. Specific information regarding access strategy, scientific case, business model, governance and ethics are thereby crucial factors for the platform
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