Integrative Problem-Solving in a Time of Decadence (eBook)

Integrative Problem-Solvingin a Time of Decadence 3
Foreword 7
Acknowledgments 19
Contents 21
Chapter 1: The Pursuit of Knowledge 31
1.1 Crossing the Gate of Night and Day 31
1.1.1 The Path from the Wise Men to the Internet 32
1.1.1.1 Hospitals of the Soul 32
1.1.1.2 Plato´s Academy and Aristotle´s Lyceum 33
1.1.1.3 From Euripides to Pier Paolo Pasolini 33
1.1.1.4 From Pope Gregory I to Pablo Picasso 34
1.1.1.5 The Internet, and Epistemic Cultures 34
1.1.2 Knowledge´s Long Promenade: From Greece and China to Modern Times 36
1.1.2.1 Emerging Issues 36
1.1.2.2 The Ionian Thinkers and Parmenides´ Poem 36
1.1.2.3 Xenophanes and the Reliability of Human Knowledge 37
1.1.2.4 Skeptics from Greece and China Enter the Scene 38
1.1.2.5 Seeking a Definition of Knowledge Through the Ages 39
1.1.3 Knowledge Classifications 42
1.1.3.1 Standard Classifications 42
1.1.3.2 Knowledge Versus Belief 43
1.1.3.3 Reality-Based Knowledge Classification 43
1.2 Matters of Scientific Knowledge 44
1.2.1 The Agent-Problem Dialectic 44
1.2.2 Napoleon´s General 45
1.2.3 The Emergence of Stochastic Reasoning 46
1.2.3.1 Scientific Reasoning and Formal Logic 47
1.2.3.2 Changing the Thinking Mode 48
1.2.3.3 The Prime Role of Natural Laws 49
1.2.3.4 The Metalanguage 50
1.2.3.5 Inference Under Conditions of Uncertainty 53
1.2.3.6 The Symbiosis of Natural Laws and Stochastic Logic 54
1.2.3.7 Experiment and Theory 54
1.2.4 The Good, the True, and the Beautiful 55
1.2.5 The Broad Context of IPS 56
1.3 A Time of Decadence 57
1.3.1 Investigator Awareness 58
1.3.2 From Ancient to Modern Barbarians 59
1.3.3 The Disregard of History 61
1.3.3.1 The Thieves of Baghdad 61
1.3.3.2 Torah´s Worry of Leaders 62
1.3.4 Corruptio Optimi Pessima 63
1.3.4.1 The Myth of the People 63
1.4 The Shadow Epistemology 65
1.4.1 Insiders Versus Public Domain Knowledge 66
1.4.2 Metarules: Cortigiani, vil Razza Dannata 67
1.4.3 The Straussian Worldview 69
1.4.4 The Ultimate Blackmail 71
1.4.5 Papa Stalin´s Motto and the Beggar´s Waltz 72
1.4.6 Elambdaomega eta Pilambdaiota! 74
1.5 The Unholy Alliance of Corporatism and Postmodernism in Higher Education 75
1.5.1 The Postmodern Corporatism University 75
1.5.2 The Lost Possibility of Experiencing Themselves 79
1.5.3 What St. Augustine and Prophet Muhammad had in Common 80
1.5.4 Politicians, the Professoriat, and Einstein´s Mule 83
1.5.5 Citizens with Market Value Versus Social Capital 84
1.5.6 Corporatism´s Failure, and Its Effects on PCU 85
1.5.7 Delenda est Carthago, and the Mythical Phoenix 88
1.6 On the Road to Damascus 89
1.6.1 Beyond Complete Comprehension but Not Completely Beyond Comprehension 90
1.6.1.1 The Paradoxical Role of Human Agent 90
1.6.1.2 Concerning Uncertainty 91
1.6.1.3 Problem Multidisciplinarity 91
1.6.2 Waiting for Godot 92
1.6.2.1 The State of Cognitive Dissonance 93
1.6.2.2 Public Confidence 94
1.6.3 The Creation of Ethics-Free Zones 95
1.6.3.1 The Diminishing Role of Constructive Criticism, and the Dominance of Indifference 95
1.6.3.2 An nescis, mi fili, quantilla sapientia mundus regatur? 97
1.6.4 Catharsis and Sophocles´ Electra 98
1.7 On Measurement and Observation 98
1.7.1 Important Distinctions 98
1.7.2 When a Number Is Not Just a Number 99
1.7.2.1 Digging Deeper: Conditions, Content, Meaning, and Operations 100
1.7.2.2 The Action of Measurement and Its Quantitative Representation 100
1.7.3 We Are That Which Asks the Question 101
1.7.3.1 Observer Versus Actor 102
1.7.3.2 Matters of Interpretation 103
1.7.3.3 Measurement and Existence 104
1.8 Feynman´s Wine and the No-Man´s Land 105
1.8.1 A Need for Synthesizing Thinkers of Large Scope 106
1.8.1.1 Multidisciplinarity and Knowledge Synthesis 106
1.8.1.2 Flying Blind Among Mountains of Diverse Knowledge 107
1.8.1.3 The Value of Empathy 108
1.8.2 When Microscale Research Is Not Miniaturized Macroscale Research 109
1.8.2.1 Open and Closed Systems 109
1.8.2.2 The River, the Bucket, and the IOED 110
1.8.3 Identity of Composition Versus Identity of Definition 111
1.8.3.1 Interdisciplinary and Intradisciplinary Composition 111
1.8.3.2 Emergence: ``Is´´ Versus ``Made Up´´ 112
1.8.4 The Para-Oedipal Act 113
1.8.4.1 Thor´s Goats 113
1.8.4.2 The ``Anti-Matthew Effect and Esotericism´´ 114
1.8.4.3 The Ultimate Contradiction: Risk-Free Research 115
1.8.4.4 Turf Protectionism 116
1.8.5 Johst´s Browning and Wollstonecraft´s Complaint 117
1.8.5.1 The Convenient Role of Bureaucrats 117
1.8.5.2 Favoring Technicians over Thinkers 118
1.8.5.3 Ignore It at Your Peril 120
1.9 About Models, Modeling, and Modelers 120
1.9.1 Real-World and Mental Processing 120
1.9.1.1 The Anthropocentric Factor 121
1.9.1.2 The Brain-Mind Debate 121
1.9.2 The Language of Nature 122
1.9.2.1 The Relationship Between Mental Constructs and Reality 122
1.9.2.2 Mathematics of IPS 123
1.9.3 Reality Does Not Have to Be Beautiful, but Models Do 124
1.9.3.1 Modeling as Theatrical Performing 125
1.9.3.2 Poetry´s Link to Modeling 126
1.9.3.3 Exploring Art-Science-Philosophy Interactions 127
1.10 Reinventing the University and a New Enlightenment 129
1.10.1 PCU´s Focus on Lower Needs, and the Challenges of Twenty-First Century 129
1.10.2 A Student-Mission, Not a Student-Customer 130
1.10.3 A New Enlightenment 131
1.11 Nonegocentric Individualism in IPS 133
1.11.1 Critical Questions and the Emergence of Epibraimatics 134
1.11.2 Egocentric Individualism and Its Problems 134
1.11.3 Nonegocentric Individualism and King Minos´ Labyrinth 137
1.11.4 Challenges Faced by Epibraimatics 139
Chapter 2: Problem-Solving Revisited 141
2.1 The Role of Philosophy in IPS 141
2.1.1 Factual and Conceptual Features 141
2.1.2 Synthesis of Philosophical and Scientific Perspectives 142
2.2 Historical Perspectives: From Heraclitus to Kuhn 143
2.2.1 Heraclitus´ River 144
2.2.2 Parmenides Apology 144
2.2.3 Socrates´ Maieutic 145
2.2.4 Plato´s Forms and Value Invariance 145
2.2.5 Aristotle´s Philosophy of Depths 146
2.2.6 Descartes´ Cogito, Ergo Sum 147
2.2.7 Spinoza´s Omni Determinatio Est Negatio 148
2.2.8 Locke´s Tabula Rasa 148
2.2.9 Hume´s Skepticism 149
2.2.10 Kant´s Synthesis 149
2.2.11 Hegel´s Dialectics 150
2.2.12 Darwin´s Evolutionary Adaptation 151
2.2.13 Wittgenstein´s Living Practice 151
2.2.14 Popper´s Constructive Criticism 152
2.2.15 Kuhn´s Paradigm 152
2.3 Rethink Everything 154
2.3.1 Che Fece Il Gran Rifiuto 154
2.3.1.1 In Berlin You Will not Fit in 154
2.3.1.2 The Big Yes and the Big No 155
2.3.1.3 The Need for a Fresh Look 156
2.3.2 Problem Formulation and Solution Meaning: Einstein´s 19/20 Rule 157
2.3.2.1 Travelers´ Tales in Cancer Research 157
2.3.2.2 The Sequence 158
2.3.2.3 Questions of Meaning 159
2.3.2.4 The ``Cargo´´ Solution 161
2.3.3 Taking Stock: Four Key Elements 162
2.3.4 Different Kinds of Problem-Solutions 163
2.3.4.1 Problem-Solution Realizability 163
2.3.4.2 Open and Closed Systems Revisited 163
2.4 Va, Pensiero, Sull´ Ali Dorate 164
2.4.1 The Color That Fills in the Missing Data Gaps 165
2.4.2 The Essence of Metaphor 166
2.5 Too Many Data-Too Little Sense, Mr. Grandgrind 167
2.5.1 The Datacentric Worldview and Its Perils 168
2.5.2 Empty Cliches and the Illuminati 169
2.5.3 The Didactic Case of the Deutsche Physik 172
2.5.4 The Glass and the Mirror 172
2.6 Paradigm and Via Negativa 173
2.6.1 The Decisive Role of the Paradigm 173
2.6.1.1 Goodnight Mr. Greenspan 174
2.6.1.2 Euclid´s Contribution and Marx´s Historical Observation 175
2.6.1.3 The Role of Consciousness in Scientific Explanation 176
2.6.1.4 Critical and Creative Thinking Modes 177
2.6.2 Learning Through Unlearning: Like Howling Bullets at Crux Moments 177
Chapter 3: Emergence of Epibraimatics 179
3.1 The Living Experience Outlook 179
3.1.1 Epistemic Context and Deep Theory 180
3.1.2 Mathematical Formulation of Knowledge Synthesis 181
3.1.3 Thinking ``Outside the Box´´ 182
3.2 The Background of Synthesis 183
3.2.1 Evolutionary Theories of Knowledge 183
3.2.2 Cognition 185
3.2.3 Consciousness, Qualia, and Intentionality 187
3.2.3.1 Human Consciousness and Qualia 188
3.2.3.2 Concerning Intentionality 189
3.2.4 Cybernetics 190
3.2.5 Epibraimatics´ Synthesis 191
3.3 Brain as an Apparatus with Which We Think We Think 191
3.3.1 A Bridge Between Nature and Humankind 191
3.3.2 The Role of Philosophy 192
3.4 If Plato Were Alive 194
3.4.1 IPS That Fits Mental Functions 194
3.4.2 Quantitative Representation of Mental Functions 195
3.4.3 Brain Parts and Their Activities 196
3.4.4 Learning from Brain Activities 198
3.5 Fundamental IPS Postulates 199
3.5.1 Concerning the CoP 201
3.5.2 Concerning the CP 202
3.5.3 Concerning the TP 204
3.5.4 Concerning the AP 205
3.5.5 Parmenides´ Gate and Morrison´s Doors 206
3.6 Knowledge Bases 207
3.6.1 Knowledge Classifications 207
3.6.1.1 The G-KB 208
3.6.1.2 The S-KB 209
3.6.1.3 Justifications of Basic Knowledge Classification 211
3.6.1.4 Other Kinds of Knowledge Classification 212
3.6.2 The Sant´Alvise Nuns in Old Venice 213
3.6.3 Papists and Experimentalists 215
3.6.4 KB Consistency 216
3.7 Problem-Solutions Suspended in Language 218
3.7.1 George Steiner´s Perspective 219
3.7.2 On Metalanguage 219
3.7.3 Niels Bohr´s Epistemology of Modern Science 220
3.8 When Truth Is Bigger Than Proof 222
3.8.1 Ignoramus vel Ignorabimus 222
3.8.1.1 The End of a Dream 223
3.8.1.2 Truth Is Bigger Than Proof 223
3.8.1.3 A Reasonable Compromise 224
3.8.2 The Case of Multidisciplinarity 225
3.9 The Structure of Knowledge 226
3.9.1 About the Way Knowledge Is Claimed and Constructed 226
3.9.2 Epistemic Standards of Knowledge 227
3.9.3 Psychological Issues of Knowledge 229
3.10 A Fusion of Ideas and Functions: A Man´s Ithaca 230
3.10.1 Thinking in Literary Terms 230
3.10.2 Licentia Poetica 231
3.10.3 The Augsburg Man 232
3.10.4 Reviewing Old Ideas in New Contexts 233
Chapter 4: Space-Time and Uncertainty 235
4.1 The ``Canvas Vs. Parenthood´´ Dilemma 235
4.1.1 Making Progress One Funeral After Another 235
4.1.2 The Sea of Space and Time 236
4.2 Space-Time Domain and Its Characterization 237
4.2.1 Greek and Hebrew Conceptions of Space-Time 238
4.2.2 Space-Time Continuum 239
4.2.3 Space as a Mode of Thought 240
4.2.4 The Meaning of Time 240
4.2.5 The Space-Time Metric 241
4.2.6 Separable Metric Structure 242
4.2.7 Composite Metric Structure 243
4.2.8 Fractal Metric Structure 245
4.2.9 The Informativeness of Metrics 246
4.3 Dealing with Uncertainty 247
4.3.1 Kundera´s Paths in the Fog 247
4.3.2 Toward an Anthropology of Uncertainty 248
4.3.2.1 Uncertainty and Human Existence in the Real-World 248
4.3.2.2 Cézanne´s and Godard´s Conceptions of Uncertainty 250
4.3.2.3 Uncertainty in Politics and Business 250
4.3.2.4 Natural and Mental States 251
4.3.3 Uncertainty and Structure in Aristotle´s Poetics 252
4.3.4 Uncertainty as an Ingredient of Creativity 253
4.3.4.1 Metternich Vs. Socrates 254
4.3.4.2 How Much Creativity Is Safe? The Case of Hypassus 255
4.4 Probability and Its Interpretations 255
4.4.1 The History of a Concept 256
4.4.2 Abstraction and Interpretation 257
4.4.3 Kolmogorov´s Formal Approach and Its Interpretive Incompleteness 257
4.4.3.1 Kolmogorov´s Axioms 258
4.4.3.2 Interpretive Incompleteness: Connecting Theory with Practice 259
4.4.4 Physical, Epistemic, Subjective, and Quantum Probabilities 260
4.4.4.1 Physical Probability 260
4.4.4.2 Epistemic Probability 261
4.4.4.3 Subjective Probability 262
4.4.4.4 Quantum Probability 263
4.4.5 In Search of the Ultimate Interpretation 264
4.4.6 The Role of Metalanguage 266
4.4.7 Probabilities of Discrete-Valued and Continuous-Valued Attributes 267
4.5 Quantitative Representations of Uncertainty 269
4.5.1 Linear Uncertainty Model 270
4.5.2 Logarithmic Uncertainty Model 271
Chapter 5: Stochastic Reasoning 273
5.1 Lifting Isis´ Veil 273
5.2 Reasoning in a Stochastic Setting 274
5.2.1 Basic Reasoning Modes 275
5.2.1.1 Elements of Reasoning 275
5.2.1.2 Deductive Reasoning 277
5.2.1.3 Inductive Reasoning 279
5.2.1.4 Hypothetico-Deductive Reasoning 280
5.2.2 Transition to Stochastic Thinking 281
5.2.2.1 A Slippery Affair and Its Psychology Connections 281
5.2.2.2 The Relationship Between Logic and Psychology 283
5.2.2.3 Some Distinctions 284
5.2.2.4 Interpretive Matters 285
5.3 The Spatiotemporal Random Field Concept 287
5.3.1 The Possible Worlds Representation: Epicurus, Leibniz, and Voltaire 287
5.3.2 Causality-Randomness Interaction 288
5.3.2.1 Agents Who Are Not Mute in Their Souls 288
5.4 Stochastic Characterization 290
5.4.1 The Holy Grail 290
5.4.2 Multiple Conceptual Layers 291
5.4.3 Robert Frost´s Moment of Choice, and the Case of Paradoxes 292
5.4.3.1 The Road Not Taken 293
5.4.3.2 The Case of Apparent Paradoxes 293
5.5 About Laws, Power Holders, and Rembrandt´s Paintings 294
5.5.1 Deterministic Laws 295
5.5.2 Statistical Laws 295
5.5.3 Stochastic Laws 296
5.5.4 Comparative Summary 297
5.6 Constructing Multivariate PDF Models 298
5.6.1 Formal Construction: Copulas and Factoras 298
5.6.1.1 Ready-Made and Tractable PDF Models 299
5.6.1.2 Copula-Based PDF Models 300
5.6.1.3 Factora-Based PDF Models 302
5.6.1.4 Comparative Comments and Pontius Pilate´s Evasion 304
5.6.2 Substantive Construction 304
5.6.2.1 The Stochastic Equations Method 305
5.6.2.2 The Knowledge Synthesis Method 306
5.6.3 Drunkard´s Search 307
5.7 Spatiotemporal Dependence and Woody Allen´s Prose 308
5.7.1 Dependence in Terms of Stochastic Expectation 308
5.7.1.1 Abstract and Intuitive Appraisals of Reality 309
5.7.1.2 Concerning Mainstream Dependence Functions 310
5.7.1.3 The Indiscrimination Property 311
5.7.2 Dependence in Terms of Natural Laws 313
5.7.3 The Predictability Power of a Model 314
5.7.4 Information Theoretic and Copula Dependence Functions 315
5.7.5 Spatiotemporal Homostationarity 318
5.8 A Generalized View of S/TRF 319
5.8.1 Random Fields Based on Generalized Functions or Distributions 319
5.8.2 An Operational Treatment of Space-Time Heterogeneous Attributes 320
5.8.3 Spatiotemporal Dependence and Heterogeneity Parameters 322
5.8.3.1 Generalized Space-Time Dependence Models 323
5.8.3.2 On Fractal Space-Time Models 323
5.8.3.3 Physical Interpretation of the Heterogeneity Parameters 325
5.9 Constructive Symbiosis and Its Problems 326
Chapter 6: Stochastic Calculus 331
6.1 Merging Logic and Stochasticity 331
6.1.1 Reflections Along the Lakeshore 331
6.1.2 From Chrysippus to Frege 332
6.1.2.1 The Context- and Content-Free Character of Formal Logic 332
6.1.2.2 Russell and Putnam Enter the Scene 334
6.1.3 The Substantive Character of Stochastic Calculus 335
6.1.3.1 Content- and Context-Dependency of Stochastic Calculus 335
6.1.4 Deduction as a Component of Stochastic Reasoning 339
6.1.5 Stochastic Falsification Principle 342
6.1.6 Reasoning with Shadow Statements, and Esprit de Finesse 342
6.2 Probability Evolution: Conditionals as Quantified Adaptation 344
6.2.1 The Horse Before the Cart 344
6.2.2 Conditionals in a Stochastic Reasoning Milieu 345
6.2.2.1 The Standard Conditional 345
6.2.2.2 Nonstandard Conditionals 346
6.2.2.3 Relationships Between Conditionals 347
6.2.2.4 A Geometrical Representation 347
6.2.3 Formulas of Stochastic Calculus 348
6.3 The Role of Specificatory Evidence in Probability 351
6.3.1 Reverend Bayes and His Critics 352
6.3.1.1 Interpretive Matters 353
6.3.1.2 Criticisms of Bayesianism 353
6.3.2 Good´s Varieties of Bayesians and De Gaulle´s Varieties of Cheese 356
6.3.3 Extra Bayesian Nulla Salus 358
6.3.4 Contextual Alternatives: Isocrates´ Concern 359
6.3.4.1 Substantive Conditionals 359
6.3.5 Conditional Dependence Indicator 360
6.3.6 William James' Sea of Possibilities 361
6.4 Vincere Scis, Hannibal-Victoria Uti Nescis 362
6.4.1 Changing the Way One Thinks One Does What One Does 363
6.4.2 Waltz of Lost Dreams? 364
Chapter 7: Operational Epibraimatics 367
7.1 The Clouds of Dublin and the IPS Dualism 367
7.1.1 Theorizing and Correlating 367
7.1.2 IPS as Knowledge Synthesis 369
7.2 The Value of Things 370
7.2.1 The Boltzmann-Laplace Relationship 370
7.2.1.1 Trade-off Relationship Between Uncertainty and Probability 371
7.2.1.2 The Uncertainty-Information Relationship 372
7.2.2 Technical Features of Information 373
7.2.3 Contextual Features of Information 374
7.2.4 It Is Not Where One Takes Things from, It Is Where One Takes Them to 375
7.2.4.1 Expected Information as Entropy 376
7.2.4.2 Comparing Entropies 376
7.2.5 Entropy in a Space-Time Continuum 377
7.2.6 What Herodotus Knew 379
7.3 Quantification of the Postulates: Fusing Form and Content 381
7.3.1 The Plurality Concept: Learn from the Future Before It Happens 381
7.3.1.1 Formal Expression and Visual Representation 381
7.3.1.2 A Linguistic Analogy 383
7.3.2 Knowledge Is About Connecting Minds, Not Merely About Collecting Data 384
7.3.2.1 Translating Knowledge into Operators 385
7.3.2.2 Knowledge Operators for Multidisciplinary Problems 386
7.3.3 Teleologic Operator: The Machine and the Artist 389
7.3.3.1 Information Seeking 389
7.3.3.2 Formalization and Its Merits 390
7.3.3.3 The Case of Myopic Vision 391
7.3.3.4 A Three-Place Relation 391
7.3.4 Adaptation Operator: The Critical Roles of Content and Consistency 392
7.3.4.1 Adaptation Types 392
7.3.4.2 Adaptation Context 393
7.3.4.3 The Role of Consistency 394
7.3.4.4 Conditionals of Reasoned Facts and Mark Twain´s Cat 395
7.3.5 Synergetic Action of the Operators 398
7.3.5.1 Blending TP and AP Operators 398
7.3.5.2 Cognitive and Evolutionary Elements of the Operators 398
7.4 Mathematical Space-Time Formulation of IPS 400
7.4.1 Equations on a Napkin 400
7.4.2 Eos and Relative KB Informativeness 402
7.4.3 Working Out the Equations 403
7.5 The Special Case of Bayesian Maximum Entropy 405
7.5.1 The BME Equations 405
7.5.2 In Situ Solution of the BME Equations 407
7.5.3 Generality of the Fundamental Equations 408
7.6 Space-Time Prediction: Tibet´s Oracle and Other Stories 410
7.6.1 Superposition Property and the Cubist Movement 410
7.6.2 Distinctions from Mainstream Data-Driven Techniques 411
7.6.3 How to Look and How to See 413
7.7 Problem-Solution Accuracy 415
7.7.1 The Geese of the Capitoline Hill and the Wise Confucius 415
7.7.2 Accuracy in Terms of Prediction Error 417
7.7.3 Solution Accuracy as a Doubt Generator 419
7.8 Space-Time Analysis in a Broader Context 420
7.8.1 Space-Time Estimation via Regression, Kriging and Machine Learning 421
7.8.2 Space-Time Estimation as Knowledge Synthesis 423
7.8.3 Afflatus Divinus 425
Chapter 8: On Model-Choice 427
8.1 Living in Plato´s Cave 427
8.1.1 Conditions of Model-Choice, the Blind Prophet, and Slavoj Zizek 427
8.1.2 Explanation Versus Fitness 430
8.2 Issues of Concern 431
8.2.1 Nature of Candidate Models and Balzac´s Wild Ass´s Skin 432
8.2.2 Optimal Data Fitting 433
8.2.3 From Occam’s Razor To Rovespiere’s Gilotine 435
8.2.4 On Predictability 437
8.3 Ideals of Model-Choice 438
8.3.1 Contextual Appropriateness 439
8.3.2 Quantitative Representations 440
8.3.2.1 Integrative Model-Choice 440
8.3.2.2 The Nonuniqueness of Mathematical Representations 442
8.3.2.3 A Matter of Methodology Rather than Metaphysics 443
8.4 Bias and Hyperreality in Model-Choice 444
8.4.1 Injustice as an Indicator of Lack of Civilization 445
8.4.2 Jean Baudrillard´s Simulacrum 445
8.4.2.1 Simulacra in Finance and Politics 446
8.4.2.2 Congregatio de Propaganda Fide 446
8.4.3 Manus Manum Lavat 448
8.4.3.1 The Post-Science Era and Carmen Electra 449
8.4.3.2 Weak States of Scientific Development 450
8.4.3.3 Charlie Chaplin´s Incident 452
8.4.4 Sir Laurence Olivier´s ``Stardom,´´ and Bette Davis´ ``Big way´´ 452
8.4.4.1 A ``Bigger-than-Life´´ Showbiz Cult 452
8.4.4.2 Faster than the New Orleans Levees 454
8.4.4.3 Oscar Wilde´s ``De Profundis´´ 455
Chapter 9: Implementation and Technology 456
9.1 ``Thinking About´´ Versus Merely ``Searching for´´ a Problem-Solution 456
9.1.1 The Role of Software Codes: Duco Ergo Sum? 457
9.1.2 The User-Software Relationship 459
9.2 The Need for Creative Participation 460
9.2.1 Ezra Pound and the Prince of Darkness 460
9.2.2 Data Versus Interpretational Uncertainty, and Descartes´ Skull 461
9.2.3 The Man and the Hammer 462
9.2.4 George Bernard Shaw´s Apple and Scientific Software 463
9.3 Yet Another Look at IPS 465
9.3.1 Thoth´s Technology and Tammuz´s Critical Thinking 465
9.3.2 Bella Gerant Alii, Tu, Felix Austria, Nube 466
9.3.3 Other Aspects of Problem-Solving 467
9.3.3.1 Polishing Existing Apples and Building Castles in the Air 467
9.3.3.2 Integrative Problem-Solving in War Zones 469
9.3.3.3 The Victorious Romans, Black Death, and Monkey Drowning 469
9.3.3.4 Try, Fail, Try Again, Fail Better 470
9.4 Marketplace of Ideas, and Tales of Misapplied Statistics 471
9.4.1 The ``Let the Data Speak´´ Mindset and the PDD Doctrine 473
9.4.1.1 The Brain-Numbing Era 473
9.4.1.2 PDD Versus Science-Based Statistics 475
9.4.1.3 Liberated Through Submission 476
9.4.2 Neglect of the Real 478
9.4.3 The ``John Treats - John Drinks´´ Approach 480
9.4.4 Matters of Lifestyle 481
9.4.5 The Papier-Mâché of PDD Analysis 482
9.5 Born an Original, Dying a Copy? 484
Chapter 10: Epilogue 486
10.1 Knowledge Pursued in Depth and Integrated in Breadth 486
10.1.1 Not ``That´´ but ``That by´´ Which We Know 486
10.1.2 To Find Out About Life, One Has to Model Life Itself 488
10.1.3 La Divina Element of IPS 489
10.2 The Ionian Tradition in a Time of Decadence 490
10.2.1 Castoriadis´ Space for Thought 491
10.2.2 Nietzsche´s Good Enemies 492
10.2.3 A Phase of Decomposition 492
10.3 The ``Socrates or Galileo´´ Dilemma 493
10.4 Like Travelers of the Legendary Khorasan Highway 494
10.5 Waiting For The Master of Ceremonies 496
10.6 A Matter of ``E Znu´´ Rather than Merely ``Znu´´ 498
References 501
Index 535