282 research outputs found

    Seeing ethnographically: teaching ethnography as part of CSCW

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    While ethnography is an established part of CSCW research, teaching and learning ethnography presents unique and distinct challenges. This paper discusses a study of fieldwork and analysis amongst a group of students learning ethnography as part of a CSCW & design course. Studying the students’ practices we explore fieldwork as a learning experience, both learning about fieldsites as well as learning the practices of ethnography. During their fieldwork and analysis the students used a wiki to collaborate, sharing their field and analytic notes. From this we draw lessons for how ethnography can be taught as a collaborative analytic process and discuss extensions to the wiki to better support its use for collaborating around fieldnotes. In closing we reflect upon the role of learning ethnography as a practical hands on – rather than theoretical – pursuit

    Philharmonic and Concert Band

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    Kennesaw State University School of Music presents Philharmonic and Concert Band.https://digitalcommons.kennesaw.edu/musicprograms/1335/thumbnail.jp

    Stock markets, credit markets, and technology-led growth

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    The high-tech sector accounts for the majority of corporate innovation in modern economies. In a sample of 38 countries, we document a strong positive relation between the initial size of the country\u27s high-tech sector and subsequent rates of GDP and total factor productivity growth. We also find a strong positive connection between a country\u27s equity (but not credit) market development and the size of its high-tech sector. Our main difference-in-differences estimates show that better developed stock markets support faster growth of innovative-intensive, high-tech industries. The main channels for this effect are higher rates of productivity and faster growth in the number of new high-tech firms. Credit market development fosters growth in industries that rely on external finance for physical capital accumulation but is unimportant for growth in innovation-intensive industries. These findings show that stock markets and credit markets play important but distinct roles in supporting economic growth. Stock markets are uniquely suited for financing technology-led growth, a particularly important concern for advanced economies

    What promotes R&D? Comparative evidence from around the world

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    R&D drives innovation and productivity growth, but appropriability problems and financing difficulties likely keep R&D investment well below the socially optimal level, particularly in high- technology industries. Though countries around the world are increasingly interested in using tax incentives and other policy initiatives to address this underinvestment problem, there is little empirical evidence comparing the effectiveness of alternative domestic policies and institutions at spurring R&D. Using data from a broad sample of OECD economies, we find that financial market rules that improve accounting standards and strengthen contract enforcement share a significant positive relation with R&D in more innovative industries, as do stronger legal protections for intellectual property. In contrast, stronger creditor rights and more generous R&D tax credits have a negative differential relation with R&D in more innovative industries. These results suggest that domestic policies directly dealing with appropriability and financing problems may be more effective than traditional tax subsides at promoting the innovative investments that drive economic growth

    What if Firms Could Borrow More? Evidence from a Natural Experiment

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    We study the effects of a unique lending program initiated by the Swedish government at the height of the financial crisis that allowed firms to suspend payment of all labor-related taxes and fees. Comprehensive administrative data on all Swedish firms show that firms borrowing from the program have higher rates of debt growth, investment spending, and employment growth compared to otherwise similar firms whose labor taxes were sufficiently low they could not benefit from the program. These results connect the availability of external credit with real activity in entrepreneurial firms in a way that has proved difficult in other settings

    Philharmonic and Concert Band

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    Kennesaw State University School of Music presents Philharmonic and Concert Band.https://digitalcommons.kennesaw.edu/musicprograms/1356/thumbnail.jp

    A jump-growth model for predator-prey dynamics: derivation and application to marine ecosystems

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    This paper investigates the dynamics of biomass in a marine ecosystem. A stochastic process is defined in which organisms undergo jumps in body size as they catch and eat smaller organisms. Using a systematic expansion of the master equation, we derive a deterministic equation for the macroscopic dynamics, which we call the deterministic jump-growth equation, and a linear Fokker-Planck equation for the stochastic fluctuations. The McKendrick--von Foerster equation, used in previous studies, is shown to be a first-order approximation, appropriate in equilibrium systems where predators are much larger than their prey. The model has a power-law steady state consistent with the approximate constancy of mass density in logarithmic intervals of body mass often observed in marine ecosystems. The behaviours of the stochastic process, the deterministic jump-growth equation and the McKendrick--von Foerster equation are compared using numerical methods. The numerical analysis shows two classes of attractors: steady states and travelling waves.Comment: 27 pages, 4 figures. Final version as published. Only minor change

    Carotid stenting: is there an operator effect? A pooled analysis from the carotid stenting trialists' collaboration.

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    BACKGROUND AND PURPOSE: Randomized clinical trials show higher 30-day risk of stroke or death after carotid artery stenting compared with surgery. We examined whether operator experience is associated with 30-day risk of stroke or death in the Carotid Stenting Trialists' Collaboration database. METHODS: The Carotid Stenting Trialists' Collaboration is a pooled individual patient database including all patients recruited in 3 randomized trials of stenting versus endarterectomy for symptomatic carotid stenosis (Endarterectomy Versus Angioplasty in patients with Symptomatic Severe Carotid Stenosis trial, Stent-Protected Angioplasty versus Carotid Endarterectomy trial, and International Carotid Stenting Study). Lifetime carotid artery stenting experience, lifetime experience in stenting procedures excluding the carotid, and annual number of procedures performed within the trial (in-trial volume), divided into tertiles, were used to measure operator experience. The outcome event was the occurrence of any stroke or death within 30 days of the procedure. The analysis was done per protocol. RESULTS: Among 1546 patients who underwent carotid artery stenting, 120 (7.8%) had a stroke or death within 30 days of the procedure. The 30-day risk of stroke or death did not differ according to operator lifetime carotid artery stenting experience (P=0.8) or operator lifetime stenting experience excluding the carotid (P=0.7). In contrast, the 30-day risk of stroke or death was significantly higher in patients treated by operators with low (mean ≤3.2 procedures/y; risk 10.1%; adjusted risk ratio=2.30 [1.36-3.87]) and intermediate annual in-trial volumes (3.2-5.6 procedures/y; 8.4%; adjusted risk ratio=1.93 [1.14-3.27]) compared with patients treated by high annual in-trial volume operators (>5.6 procedures/y; 5.1%). CONCLUSIONS: Carotid stenting should only be performed by operators with annual procedure volume ≥6 cases per year

    Early Endarterectomy Carries a Lower Procedural Risk Than Early Stenting in Patients With Symptomatic Stenosis of the Internal Carotid Artery: Results From 4 Randomized Controlled Trials.

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    BACKGROUND AND PURPOSE: Patients undergoing carotid endarterectomy (CEA) for symptomatic stenosis of the internal carotid artery benefit from early intervention. Heterogeneous data are available on the influence of timing of carotid artery stenting (CAS) on procedural risk. METHODS: We investigated the association between timing of treatment (0-7 days and >7 days after the qualifying neurological event) and the 30-day risk of stroke or death after CAS or CEA in a pooled analysis of individual patient data from 4 randomized trials by the Carotid Stenosis Trialists' Collaboration. Analyses were done per protocol. To obtain combined estimates, logistic mixed models were applied. RESULTS: Among a total of 4138 patients, a minority received their allocated treatment within 7 days after symptom onset (14% CAS versus 11% CEA). Among patients treated within 1 week of symptoms, those treated by CAS had a higher risk of stroke or death compared with those treated with CEA: 8.3% versus 1.3%, risk ratio, 6.7; 95% confidence interval, 2.1 to 21.9 (adjusted for age at treatment, sex, and type of qualifying event). For interventions after 1 week, CAS was also more hazardous than CEA: 7.1% versus 3.6%, adjusted risk ratio, 2.0; 95% confidence interval, 1.5 to 2.7 (P value for interaction with time interval 0.06). CONCLUSIONS: In randomized trials comparing stenting with CEA for symptomatic carotid artery stenosis, CAS was associated with a substantially higher periprocedural risk during the first 7 days after the onset of symptoms. Early surgery is safer than stenting for preventing future stroke. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00190398; URL: http://www.controlled-trials.com. Unique identifier: ISRCTN57874028; Unique identifier: ISRCTN25337470; URL: http://www.clinicaltrials.gov. Unique identifier: NCT00004732

    Prediction Models for Clinical Outcome After a Carotid Revascularization Procedure.

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    Background and Purpose- Prediction models may help physicians to stratify patients with high and low risk for periprocedural complications or long-term stroke risk after carotid artery stenting or carotid endarterectomy. We aimed to evaluate external performance of previously published prediction models for short- and long-term outcome after carotid revascularization in patients with symptomatic carotid artery stenosis. Methods- From a literature review, we selected all prediction models that used only readily available patient characteristics known before procedure initiation. Follow-up data from 2184 carotid artery stenting and 2261 carotid endarterectomy patients from 4 randomized trials (EVA-3S [Endarterectomy Versus Angioplasty in Patients With Symptomatic Severe Carotid Stenosis], SPACE [Stent-Protected Angioplasty Versus Carotid Endarterectomy], ICSS [International Carotid Stenting Study], and CREST [Carotid Revascularization Endarterectomy Versus Stenting Trial]) were used to validate 23 short-term outcome models to estimate stroke or death risk ≤30 days after the procedure and the original outcome measure for which the model was developed. Additionally, we validated 7 long-term outcome models for the original outcome measure. Predictive performance of the models was assessed with C statistics and calibration plots. Results- Stroke or death ≤30 days after the procedure occurred in 158 (7.2%) patients after carotid artery stenting and in 84 (3.7%) patients after carotid endarterectomy. Most models for short-term outcome after carotid artery stenting (n=4) or carotid endarterectomy (n=19) had poor discriminative performance (C statistics ranging from 0.49-0.64) and poor calibration with small absolute risk differences between the lowest and highest risk groups and overestimation of risk in the highest risk groups. Long-term outcome models (n=7) had a slightly better performance with C statistics ranging from 0.59 to 0.67 and reasonable calibration. Conclusions- Current models did not reliably predict outcome after carotid revascularization in a trial population of patients with symptomatic carotid stenosis. In particular, prediction of short-term outcome seemed to be difficult. Further external validation of existing prediction models or development of new prediction models is needed before such models can be used to support treatment decisions in individual patients
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