The economic ecology of small businesses in Oxfordshire

Report by the Oxfordshire Economic Observatory (OEO) for the Federation of Small Businesses (FSB), Oxfordshire Branch

The Role of Water Quality Perceptions in Modeling Lake Recreation Demand

Recreation demand models typically incorporate measures of the physical attributes of recreational sites; e.g., Secchi depth or phosphorous levels in case of water quality. Moreover, most studies show that individuals do respond to these physical characteristics in choosing where to recreate. However, the question remains as to whether the available physical measures accurately capture individual perceptions of water quality and if there is a additional role to be played by elicited perception measures in modeling recreation demand. In this paper, we use data from the 2004 Iowa Lakes Survey to model recreation demand as a function of both the physical water quality at 131 lakes in the state and household perceptions of lake water quality. In general, water quality perceptions are correlated with the available physical measures, but not perfectly so, and both actual and perceived water quality are found to significantly impact recreational site choice.

Valuing Water Quality As a Functionof Water Quality Measures

This paper incorporates a rich set of physical water quality attributes, as well as site and household characteristics, into a model of recreational lake usage in Iowa. Our analysis shows individuals are responsive to physical water quality measures. Willingness-to-pay estimates are reported based on improvements in these measures.

Examining the Change in Preservice Mathematics Teachers’ Conceptions and Effectiveness of Social Justice Content

This study examined preservice teachers\u27 perceptions of teaching mathematics using social justice topics to make mathematics accessible to all students. Situated at a large, public, predominantly White institution in the southeast United States, where preservice teachers are not required to take a course on teaching diverse populations, participants were asked to respond to questions surrounding their experience with a mathematical social justice activity adapted from Gutstein and Peterson (2005). Using a mixed methods approach in analyzing data from pre-and post-surveys, researchers could compare preservice mathematics teachers\u27 initial views of teaching mathematics for social justice after participating in an intervention/activity on world wealth and population disparity. Results showed that although preservice teachers\u27 attitudes shifted from more general statements to somewhat more concrete ideas surrounding the classroom environment, these students are still apprehensive about using this form of pedagogy in the future

Birds and Birding in Wyoming’s Bighorn Mountains Region

The Bighorn Mountains consist of a relatively well-isolated north-south mountain range in north-central Wyoming that had their origins during the early Cenozoic era, 50-65 million years ago. The present-day Bighorn range is more than 100 miles in length and has a maximum elevation of 13,167 feet (Cloud Peak), only slightly less than the highest peak in Wyoming (Gannett Peak, at 13,804 feet). The mountains are flanked to the west by the Bighorn River basin, and to the east by the Powder River basin, both of which support only semi-desert vegetation dominated by sagebrush. Elevations of the Powder River basin near the Montana border and the Bighorn River near Worland are below 3,700 feet, and annual precipitation at Worland averages less than ten inches annually. The nearly 10,000-foot range of regional elevations and associated climate variations have produced a wide variation of terrestrial vegetation types. The mountains are still largely covered with native grasslands and mostly coniferous forest vegetation, the latter ranging from juniper scrub at low altitudes through ponderosa and lodgepole pines at middle elevations, to subalpine fir, Engelmann spruce and limber pine transitional to alpine tundra, which begins at 9,800–11,400 feet. Most of the still-forested areas lie within the 1.1 million-acre Bighorn National Forest. We defined the Bighorn region as encompassing or about 6,800 square miles (latilong blocks 4 and 5), and determined that at least 327 bird species have been reliably reported from the region, plus 15 species of hypothetical status. This compared with a total of 427 species reported for all of Wyoming as of 2010 (Faulkner, 2010). Breeding within the region has been confirmed for 190 species. Among the breeders, 77 species have breeding ranges that were classified as to having an either clearly eastern-oriented or western-oriented affinity in North America. Of these, 55 (71 percent) were judged to be western-oriented and 22 (29 percent) eastern-oriented, indicating that the strongest zoogeographic affinities of Bighorn region birds are with western North America. Species descriptions indicate relative abundance, breeding status by latilong, locality/date records for rarer species, and other relevant information. Many regional birding areas are described and mapped, and results of recent regional breeding bird surveys and seasonal bird counts are summarized. Line drawings illustrate representatives of each of the 53 avian families documented for the region, and there are more than 60 literature citations.https://digitalcommons.unl.edu/zeabook/1017/thumbnail.jp

Unsupervised machine learning of integrated health and social care data from the Macmillan Improving the Cancer Journey service in Glasgow

Background: Improving the Cancer Journey (ICJ) was launched in 2014 by Glasgow City Council and Macmillan Cancer Support. As part of routine service, data is collected on ICJ users including demographic and health information, results from holistic needs assessments and quality of life scores as measured by EQ-5D health status. There is also data on the number and type of referrals made and feedback from users on the overall service. By applying artificial intelligence and interactive visualization technologies to this data, we seek to improve service provision and optimize resource allocation.Method: An unsupervised machine-learning algorithm was deployed to cluster the data. The classical k-means algorithm was extended with the k-modes technique for categorical data, and the gap heuristic automatically identified the number of clusters. The resulting clusters are used to summarize complex data sets and produce three-dimensional visualizations of the data landscape. Furthermore, the traits of new ICJ clients are predicted by approximately matching their details to the nearest existing cluster center.Results: Cross-validation showed the model’s effectiveness over a wide range of traits. For example, the model can predict marital status, employment status and housing type with an accuracy between 2.4 to 4.8 times greater than random selection. One of the most interesting preliminary findings is that area deprivation (measured through Scottish Index of Multiple Deprivation-SIMD) is a better predictor of an ICJ client’s needs than primary diagnosis (cancer type).Conclusion: A key strength of this system is its ability to rapidly ingest new data on its own and derive new predictions from those data. This means the model can guide service provision by forecasting demand based on actual or hypothesized data. The aim is to provide intelligent person-centered recommendations. The machine-learning model described here is part of a prototype software tool currently under development for use by the cancer support community.Disclosure: Funded by Macmillan Cancer Support</p

The pediatric emergency department care experience: A quality measure

To develop and validate a measure of the quality of the pediatric emergency department care experience from the parent perspective. This was a multiphase study conducted at a tertiary-care pediatric health system using qualitative and quantitative methods. A list of candidate questions was developed to measure each of eight dimensions of family-centered pediatric emergency care described in a published framework. This list was evaluated and refined using the Question Appraisal System (QAS-99) followed by cognitive interviewing methods. Remaining questions were field tested using survey methods via telephone interviews with randomly selected parents. Composite scores to measure each of the eight dimensions of family-centered pediatric emergency care were calculated. Reliability was evaluated using measures of internal consistency. Construct validity was evaluated by measuring the association of each question and composite scores with overall satisfaction. A pool of 77 questions was reduced to 51 using QAS-99 criteria. Cognitive interviews with 19 parents resulted in a final list of 24 questions for field testing. With a response rate of 46%, 404 parents participated in the field test. Each individual question exhibited a significant positive association with overall satisfaction. Measures of internal consistency did not support the composite scores based on the initial eight dimensions. An exploratory factor analysis resulted in alternative composite measures that exhibited acceptable reliability and construct validity. This study has resulted in a measure that can be used to inform quality improvement work aimed at improving the pediatric emergency department care experience