Volunteer Voices: Tennessee\u27s Collaborative Digitization Program

This article provides an overview of Volunteer Voices, Tennessee’s statewide digitization program. The authors focus on the three-year Institute of Museum and Library Services (IMLS) National Leadership Grant that provided the foundation for future growth of the digitization program. In addition to an overview of the content selection, metadata issues, software selection, digital preservation, and K-12 education emphasis of the grant project, the article includes a detailed description of the work done by the digitization and content specialists from across the state who selected and scanned items. The article concludes with a look at post-grant efforts to promote the sustainability of Volunteer Voices

Volunteer Voices: Tennessee’s Collaborative Digitization Program

This article provides an overview of Volunteer Voices, Tennessee’s statewide digitization program. The authors focus on the three-year Institute of Museum and Library Services (IMLS) National Leadership Grant that provided the foundation for future growth of the digitization program. In addition to an overview of the content selection, metadata issues, software selection, digital preservation, and K-12 education emphasis of the grant project, the article includes a detailed description of the work done by the digitization and content specialists from across the state who selected and scanned items. The article concludes with a look at post-grant efforts to promote the sustainability of Volunteer Voices

Should we still believe in constrained supersymmetry?

We calculate Bayes factors to quantify how the feasibility of the constrained minimal supersymmetric standard model (CMSSM) has changed in the light of a series of observations. This is done in the Bayesian spirit where probability reflects a degree of belief in a proposition and Bayes' theorem tells us how to update it after acquiring new information. Our experimental baseline is the approximate knowledge that was available before LEP, and our comparison model is the Standard Model with a simple dark matter candidate. To quantify the amount by which experiments have altered our relative belief in the CMSSM since the baseline data we compute the Bayes factors that arise from learning in sequence the LEP Higgs constraints, the XENON100 dark matter constraints, the 2011 LHC supersymmetry search results, and the early 2012 LHC Higgs search results. We find that LEP and the LHC strongly shatter our trust in the CMSSM (with $M_0$ and $M_{1/2}$ below 2 TeV), reducing its posterior odds by a factor of approximately two orders of magnitude. This reduction is largely due to substantial Occam factors induced by the LEP and LHC Higgs searches.Comment: 38 pages, 14 figures; version as published in EPJ