LEADER 01422oam 2200397z- 450 001 9910466055603321 005 20210112193526.0 010 $a1-62036-417-4 035 $a(CKB)3710000000939531 035 $a(MiAaPQ)EBC4731643 035 $a(EXLCZ)993710000000939531 100 $a20161219c2016uuuu -u- - 101 0 $aeng 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMulticulturalism on campus $etheory, models, and practices for understanding diversity and creating inclusion /$fedited by Michael J. Cuyjet, Chris Linder, Mary F. Howard-Hamilton, and Diane L. Cooper 205 $aSecond edition. 210 1$aSterling, Virginia :$cStylus Publishing,$d[2016] 215 $a1 online resource (viii, 427 pages) 606 $aMulticultural education$zUnited States 606 $aCultural pluralism$zUnited States 606 $aMinorities$xEducation (Higher)$zUnited States 606 $aEducational equalization$zUnited States 615 0$aMulticultural education 615 0$aCultural pluralism 615 0$aMinorities$xEducation (Higher) 615 0$aEducational equalization 702 $aCuyjet$b Michael J. 702 $aLinder$b Chris$f1976- 702 $aHoward-Hamilton$b Mary F. 702 $aCooper$b Diane L. 906 $aBOOK 912 $a9910466055603321 996 $aMulticulturalism on campus$92488398 997 $aUNINA LEADER 04173oam 2200733I 450 001 9910462322703321 005 20200520144314.0 010 $a1-280-68409-7 010 $a9786613661036 010 $a1-136-32308-2 010 $a0-203-12072-8 024 7 $a10.4324/9780203120729 035 $a(CKB)2670000000203413 035 $a(EBL)981854 035 $a(OCoLC)804662354 035 $a(SSID)ssj0000681748 035 $a(PQKBManifestationID)11406735 035 $a(PQKBTitleCode)TC0000681748 035 $a(PQKBWorkID)10678355 035 $a(PQKB)11577045 035 $a(MiAaPQ)EBC981854 035 $a(PPN)198460449 035 $a(Au-PeEL)EBL981854 035 $a(CaPaEBR)ebr10568510 035 $a(CaONFJC)MIL366103 035 $a(OCoLC)796827267 035 $a(EXLCZ)992670000000203413 100 $a20180706d2012 uy 0 101 0 $aeng 135 $aurcnu---unuuu 181 $ctxt 182 $cc 183 $acr 200 00$aRewards for high public office in Europe and North America /$fedited by Marleen Brans and B. Guy Peters 210 1$aLondon :$cRoutledge,$d2012. 215 $a1 online resource (328 p.) 225 1 $aRoutledge research in comparative politics ;$v49 300 $aDescription based upon print version of record. 311 $a0-415-74653-1 311 $a0-415-78105-1 320 $aIncludes bibliographical references and index. 327 $aCover; Rewards for High Public Office in Europe and North America; Copyright; Contents; Tables; Figures; Preface; Contributors; 1 Rewards for high public office: Continuing developments; 2 Rewards at the top: Cross-country comparisons across offices and over time; 3 Rewards at the top in UK central government; 4 RHPOs in Ireland: Ratcheting pay in the public sector; 5 Rewards for high public office in the United States; 6 Rewards for high public office in France: Still the century of privileges?; 7 Rewards for high public office: The case of Italy 327 $a8 Rewards for high public offices in Spain (1990-2009): Incremental changes following the pattern of the civil service9 Rewards at the top in Belgium: Uneasy struggles with transparency and variability in paying public office; 10 Rewards for high public office in the Netherlands; 11 Rewards for high public office: The case of Norway; 12 Rewards for high public office in Sweden; 13 Starting from scratch: Rewards for high public office in Estonia; 14 Rewards for high public offices in Hungary; 15 Bureaucracy and rewards in Romania 327 $a16 Into the labyrinth: The rewards for high public office in Slovakia17 Rewards at the top: The European Union; 18 Conclusion: Choosing public sector rewards; Appendix - Basic data on RHPO in 15 countries and the EU institutions; Index 330 $aAnyone observing the recent scandals in the United Kingdom could not fail to understand the political importance of the rewards of high public office. The British experience has been extreme but by no means unique, and many countries have experienced political over the pay and perquisites of public officials. This book addresses an important element of public governance, and does so in longitudinal and comparative manner. The approach enables the contributors to make a number of key statements not only about the development of political systems but also about the differences among th 410 0$aRoutledge research in comparative politics ;$v49. 606 $aPublic officers$xSalaries, etc 606 $aCivil service$xSalaries, etc 606 $aGovernment executives$xSalaries, etc 606 $aComparative government 608 $aElectronic books. 615 0$aPublic officers$xSalaries, etc. 615 0$aCivil service$xSalaries, etc. 615 0$aGovernment executives$xSalaries, etc. 615 0$aComparative government. 676 $a331.2/166 701 $aBrans$b M$g(Marleen)$0926701 701 $aPeters$b B. Guy$050137 801 0$bFlBoTFG 801 1$bFlBoTFG 906 $aBOOK 912 $a9910462322703321 996 $aRewards for high public office in Europe and North America$92081070 997 $aUNINA LEADER 10904nam 2200469 450 001 9910444452703321 005 20211006114353.0 010 $a3-030-51931-7 035 $a(CKB)5590000000437625 035 $a(MiAaPQ)EBC6509885 035 $a(Au-PeEL)EBL6509885 035 $a(OCoLC)1244628097 035 $a(PPN)25386111X 035 $a(EXLCZ)995590000000437625 100 $a20211006d2020 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEvo-seti $elife evolution statistics on earth and exoplanets. /$fClaudio Maccone 210 1$aCham, Switzerland :$cSpringer,$d[2020] 210 4$d©2020 215 $a1 online resource (lvii, 837 pages) $cillustrations 311 $a3-030-51930-9 327 $aIntro -- Preface -- Contents -- OVERCOME Theorem, that is PEAK-LOCUS Theorem, Proven by Maxima -- 1 OVERCOME Theorem, that is PEAK-LOCUS Theorem -- 2 Evo-Entropy(p): Measuring "How Much Evolution" Occurred -- 3 Perfectly LINEAR Evo-Entropy When the Mean Value Is Perfectly Exponential (A GBM): This Is just the Molecular Clock -- 4 Introducing EE, the Evo-SETI Unit: An Amount of Information Equal to the Evo-Entropy Reached by Life Evolution on Earth Nowadays -- 5 Conclusions About Evo-Entropy -- Appendix -- References -- Evo-SETI Mathematics: Part 1: Entropy of Information. Part 2: Energy of Living Forms. Part 3: The Singularity -- 1 Introduction -- 2 Part 1: Entropy of Information as the Measure of Evolution, Peak-Locus Theorem, and Scale of Biological Evolution (Evo-SETI Scale) -- 2.1 Purpose of This Chapter -- 2.2 A Simple Proof of the b-Lognormal Probability Density Function (PDF) -- 2.3 Biological Evolution as the Exponential Increase of the Number of Living Species -- 2.4 Biological Evolution on Earth Was just a Particular Realization of Geometric Brownian Motion in the Number of Living Species -- 2.5 During the Last 3.5 Billion Years Life Forms Increased like a Lognormal Stochastic Process -- 2.6 Mean Value of the Lognormal Process L(t) -- 2.7 L( t ) Initial Conditions at ts -- 2.8 L( t ) Final Conditions at te > -- ts -- 2.9 Important Special Cases of mL ( t ) -- 2.10 Boundary Conditions When mL ( t ) Is a First, Second or Third Degree Polynomial in the Time (t - ts) -- 2.11 Peak-Locus Theorem -- 2.12 Evo-Entropy(p): Measuring "How Much Evolution" Occurred -- 2.13 Perfectly Linear Evo-Entropy When the Mean Value Is Perfectly Exponential (a GBM): This Is just the Molecular Clock -- 2.14 Introducing EE, the Evo-SETI Unit: An Amount of Information Equal to the Evo-Entropy Reached by Life Evolution on Earth Nowadays. 327 $a2.15 Markov-Korotayev Alternative to Exponential: A Cubic Growth -- 2.16 Evo-Entropy of the Markov-Korotayev Cubic Growth -- 2.17 Comparing the Evo-Entropy of the Markov-Korotayev Cubic Growth to a Hypothetical (1) Linear and (2) Parabolic Growth -- 2.18 Conclusions About Evo-Entropy -- 2.19 Life as a Finite b-Lognormal as Assumed by This Author Prior to 2017 -- 2.20 b-Lognormal History Formulae and Their Applications to Past History -- 3 Part 2: Energy of Living Forms by "Logpar" Power Curves -- 3.1 Introduction to Logpar Power Curves -- 3.2 Finding the Parabola Equation of the Right Part of the Logpar -- 3.3 Finding the b-Lognormal Equation of the Left Part of the Logpar -- 3.4 Area Under the Parabola on the Right Part of the Logpar Between Peak and Death -- 3.5 Area Under the Full Logpar Curve Between Birth and Death -- 3.6 The Area Under the Logpar Curve Depends on Sigma Only, and Here Is the Area Derivative W.R.T. ? -- 3.7 Exact "History Equations" for Each Logpar Curve -- 3.8 Considerations on the Logpar History Equations -- 3.9 Logpar Peak Coordinates Expressed in Terms of ( b,p,d ) Only -- 3.10 History of Ancient Rome as an Example of How to Use the Logpar History Formulae -- 3.11 Area Under Rome's Logpar and Its Meaning as "Overall Energy" of the Roman Civilization -- 3.12 The Energy Function of d Regarded as a Function of the Death Instant d, Hereafter Renamed D -- 3.13 Discovering an Oblique Asymptote of the Energy Function, Energy(D), While the Death Instant D Is Increasing Indefinitely -- 3.14 The Oblique Asymptote for the "History of Rome" Case -- 3.15 What if Hadn't Rome Fallen? Discovering the Straight Line Parallel to the Asymptote but Starting at the Rome Power Peak -- 3.16 Energy Output of the Sun as a G2 Star Over the About 10 Billion Years of Its Lifetime -- 3.17 Energy Output of an M Star Over 45 Billion Years of Lifetime. 327 $a3.18 Mean Power in a Lifetime -- 3.19 Lifetime Mean Value -- 3.20 Logpar Power Curves Versus b-Lognormal Probability Densities -- 3.21 Conclusions About Logpars -- 4 Part 3: Before and After the Singularity According to Evo-SETI Theory -- 4.1 Every Exponential in Time Has just a Single Knee: The Instant at Which Its Curvature Is Highest -- 4.2 GBM Exponential as Mean Value of the Increasing Number of Species Since the Origin of Life on Earth -- 4.3 Deriving the Knee Time for GBMs -- 4.4 Knee-Centered Form of the GBM Exponential -- 4.5 Finding WHEN the GBM Knee Will Occur According to the Author's Conventional Values for ts and B -- 4.6 Ray Kurzweil's 2006 Book "the Singularity Is Near" -- 4.7 Kurzweil's Singularity Is the Same as Our GBM's Knee in Our Evo-SETI Theory -- 4.8 Measuring the Pace of Evolution B by the Average Number m0 of Species Living on Earth NOW -- 4.9 An Unexpected Discovery: The "Origin-to-Now" ("OTN") Equation Relating the Time of the Origin of Life on Earth (ts) to m0 (the Average Number of Species Living on Earth Right Now) -- 4.10 Solving the "Origin-to-Now" Equation NUMERICALLY for the Two Cases of -3.5 and -3.8 Billion Years of Life on Earth -- 4.11 But... Biologists Are UNABLE to Measure m0 Experimentally! -- 4.12 Lognormal pdf of the GBM -- 4.13 Finding the GBM Parameter ? -- 4.14 Numerical Standard Deviation Nowadays for the Two Cases of Life Starting 3.5 and 3.8 Billion Years Ago -- 4.15 Numerical ? for the Two Cases of Life Starting 3.5 and 3.8 Billion Years Ago -- 4.16 Conclusions -- References -- SETI, Evolution and Human History Merged into a Mathematical Model -- 1 SETI and Darwinian Evolution Merged Mathematically -- 1.1 Introduction: The Drake Equation (1961) as the Foundation of SETI -- 1.2 Statistical Drake Equation (2008) -- 1.3 The Statistical Distribution of N Is Lognormal. 327 $a1.4 Darwinian Evolution as Exponential Increase of the Number of Living Species -- 1.5 Introducing the 'Darwin' (D) Unit, Measuring the Amount of Evolution that a Given Species Reached -- 1.6 Darwinian Evolution Is just a Particular Realization of Geometric Brownian Motion in the Number of Living Species -- 2 GBM as the Key to Stochastic Evolution of All Kinds -- 2.1 The N(t) GBM as Stochastic Evolution -- 2.2 Our Statistical Drake Equation Is the Static Special Case of N(t) -- 2.3 GBM as the Key to Mathematics of Finance -- 3 Darwinian Evolution Re-defined as a GBM in the Number of Living Species -- 3.1 A Concise Introduction to Cladistics and Cladograms -- 3.2 Cladistics: Namely the GBM Mean Exponential as the Locus of the Peaks of b-Lognormals Representing Each a Different Species Started by Evolution at  Time t = b -- 3.3 Cladogram Branches Are Increasing, Decreasing or Stable (Horizontal) Exponential Arches as Functions of Time -- 3.4 KLT-Filtering in Hilbert Space and Darwinian Selection Are "the Same Thing" in Our Theory... -- 3.5 Conclusions About Our Statistical Model for Evolution and Cladistics -- 4 Lifespans of Living Beings as b-Lognormals -- 4.1 Further Extending b-Lognormals as Our Model for All Lifespans -- 4.2 Infinite b-Lognormals -- 4.3 From Infinite to Finite b-Lognormals: Defining the Death Time, d, as the Time Axis Intercept of the b-Lognormal Tangent Line at Senility s -- 4.4 Terminology About Various Time Instants Related to a Lifetime -- 4.5 Terminology About Various Time Spans Related to a Lifetime -- 4.6 Normalizing to One All the Finite b-Lognormals -- 4.7 Finding the b-Lognormals Given b and Two Out of the Four a, p, s, d -- 5 Golden Ratios and Golden b-Lognormals -- 5.1 Is ? Always Smaller Than 1? -- 5.2 Golden Ratios and Golden b-Lognormals -- 6 Mathematical History of Civilizations. 327 $a6.1 Civilizations Unfolding in Time as b-Lognormals -- 6.2 Eight Examples of Western Historic Civilizations as Finite b-Lognormals -- 6.3 Plotting All b-Lognormals Together and Finding the Trends -- 6.4 b-Lognormals of Alien Civilizations -- 7 Extrapolating History into the Past: Aztecs -- 7.1 Aztecs-Spaniards as an Example of Two Suddenly Clashing Civilizations with Large Technology Gap -- 7.2 'Virtual Aztecs' Method to Find the 'True Aztecs' b-Lognormal -- 8 b-Lognormal Entropy as 'Civilization Amount' -- 8.1 Introduction: Invoking Entropy and Information Theory -- 8.2 Exponential Curve in Time Determined by Two Points Only -- 8.3 Assuming that the Exponential Curve in Time Is the GBM Mean Value Curve -- 8.4 The 'No-Evolution' Stationary Stochastic Process -- 8.5 Entropy of the 'Running b-Lognormal' Peaked at the GBM Exponential Mean -- 8.6 Decreasing Entropy for an Exponentially Increasing Evolution: Progress! -- 8.7 Six Examples: Entropy Changes in Darwinian Evolution, Human History Between Ancient Greece and Now, and Aztecs and Incas Versus Spaniards -- 8.8 b-Lognormals of Alien Civilizations -- 9 Conclusion: Summary of Technical Concepts Described -- References -- Evolution and Mass Extinctions as Lognormal Stochastic Processes -- 1 Introduction: Mathematics and Science -- 2 A Summary of the 'Evo-SETI' Model of Evolution and SETI -- 3 Important Special Cases of mL(t) -- 4 Introducing b-lognormals -- 5 Peak-Locus Theorem -- 6 Entropy as the Evolution Measure -- 7 Evo-SETI -- 8 Mass Extinctions of Darwinian Evolution Described by a Decreasing GBM -- 8.1 GBMs to Understand Mass Extinctions of the Past -- 8.2 Example: The K-Pg Mass Extinction Extending Ten Centuries After Impact -- 9 Mass Extinctions Described by an Adjusted Parabola Branch -- 9.1 Adjusting the Parabola to the Mass Extinctions of the Past. 327 $a9.2 Example: The Parabola of the K-Pg Mass Extinction Extending Ten Centuries After Impact. 606 $aExobiology 615 0$aExobiology. 676 $a576.839 700 $aMaccone$b Claudio$0842140 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910444452703321 996 $aEvo-seti$91907141 997 $aUNINA