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Complexity theory and the social sciences : an introduction / / David Byrne
| Complexity theory and the social sciences : an introduction / / David Byrne |
| Autore | Byrne D. S (David S.), <1947-> |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | London ; ; New York, : Routledge, 1998 |
| Descrizione fisica | 1 online resource (312 pages) |
| Disciplina | 300/.1/5118 |
| Soggetto topico |
Social sciences - Mathematical models
Chaotic behavior in systems Social sciences - Research |
| ISBN |
1-134-71473-4
0-203-00391-8 0-203-15842-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Book Cover; Title; Contents; Acknowledgements; Introduction; Understanding the complex; The reality of the complex: the complexity of the real; Complexity and the quantitative programme in social science; Analysing social complexity; Complex spaces: regions, cities and neighbourhoods in a complex world; The complex character of health and illness; Complexity, education and change; Complexity and policy: the limits to urban governance; Conclusion; Glossary; Notes; Bibliography; Inde |
| Record Nr. | UNINA-9910172241703321 |
Byrne D. S (David S.), <1947->
|
||
| London ; ; New York, : Routledge, 1998 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Interpreting quantitative data [[electronic resource] /] / David Byrne
| Interpreting quantitative data [[electronic resource] /] / David Byrne |
| Autore | Byrne D. S (David S.), <1947-> |
| Pubbl/distr/stampa | London, : SAGE, 2002 |
| Descrizione fisica | 1 online resource (187 p.) |
| Disciplina | 300.72 |
| Soggetto topico |
Research
Methodology Social sciences - Statistical methods |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9786611897642
1-4462-3028-7 1-281-89764-7 1-84920-931-6 1-84860-866-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine generated contents note: Introduction 1 -- 1 Interpreting the Real and Describing the Complex: -- Why We Have to Measure 12 -- Positivism, realism and complexity 14 -- Naturalism - a soft foundationalist argument 17 -- There are no universals but, nevertheless, we can know 19 -- Models and measures: a first pass 21 -- Contingency and method - retroduction and retrodiction 25 -- Conclusion 27 -- 2 The Nature of Measurement: What We Measure and -- How We Measure 29 -- Death to the variable 29 -- State space 32 -- Classification 34 -- Sensible and useful measuring 37 -- Conclusion 41 -- 3 The State's Measurements: The Construction and -- Use of Official Statistics 44 -- The history of statistics as measures 45 -- Official and semi-official statistics 49 -- Social indicators 52 -- Tracing individuals 56 -- Secondary data analysis 57 -- Sources 57 -- Conclusion 58 -- 4 Measuring the Complex World: The Character of Social Surveys 61 -- Knowledge production - the survey as process 63 -- Models from surveys - beyond the flowgraph? 66 -- Representative before random - sampling in the real world 72 -- Conclusion 77 -- 5 Probability and Quantitative Reasoning 79 -- Objective probability versus the science of clues 80 -- Single case probabilities - back to the specific 84 -- Gold standard - or dross? 84 -- Understanding Head Start 88 -- Probabilistic reasoning in relation to non-experimental data 90 -- Randomness, probability, significance and investigation 92 -- Conclusion 93 -- 6 Interpreting Measurements: Exploring, Describing and Classifying 95 -- Basic exploration and description 96 -- Making sets of categories - taxonomy as social exploration 99 -- Can classifying help us to sort out causal processes? 105 -- Conclusion 110 -- 7 Linear Modelling: Clues as to Causes 112 -- Statistical models 113 -- Flowgraphs: partial correlation and path analysis 116 -- Working with latent variables - making things out of things -- that don't exist anyhow 117 -- Multi-level models 120 -- Statistical black boxes - Markov chains as an example 122 -- Loglinear techniques - exploring for interaction 123 -- Conclusion 128 -- 8 Coping with Non-linearity and Emergence: Simulation and -- Neural Nets 130 -- Simulation - interpreting through virtual worlds 131 -- Micro-simulation - projecting on the basis of aggregation 133 -- Multi-agent models - interacting entities 135 -- Neural nets are not models but inductive empiricists 139 -- Models as icons, which are also tools 141 -- Using the tools 142 -- Conclusion 143 -- 9 Qualitative Modelling: Issues of Meaning and Cause 145 -- From analytic induction through grounded theory to computer -- modelling - qualitative exploration of cause 147 -- Coding qualitative materials 150 -- Qualitative Comparative Analysis (QCA) - a Boolean approach 154 -- Iconic modelling 157 -- Integrative method 159 -- Conclusion 160 -- Conclusion 162 -- Down with: 162 -- Up with: 163 -- Action theories imply action164. |
| Record Nr. | UNINA-9910453283903321 |
|
Byrne D. S (David S.), <1947->
|
||
| London, : SAGE, 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Interpreting quantitative data [[electronic resource] /] / David Byrne
| Interpreting quantitative data [[electronic resource] /] / David Byrne |
| Autore | Byrne D. S (David S.), <1947-> |
| Pubbl/distr/stampa | London, : SAGE, 2002 |
| Descrizione fisica | 1 online resource (x, 176 p.) : ill |
| Disciplina | 300.721 |
| Soggetto topico |
Research
Methodology Social sciences - Statistical methods |
| ISBN |
9786611897642
1-4462-3028-7 1-281-89764-7 1-84920-931-6 1-84860-866-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine generated contents note: Introduction 1 -- 1 Interpreting the Real and Describing the Complex: -- Why We Have to Measure 12 -- Positivism, realism and complexity 14 -- Naturalism - a soft foundationalist argument 17 -- There are no universals but, nevertheless, we can know 19 -- Models and measures: a first pass 21 -- Contingency and method - retroduction and retrodiction 25 -- Conclusion 27 -- 2 The Nature of Measurement: What We Measure and -- How We Measure 29 -- Death to the variable 29 -- State space 32 -- Classification 34 -- Sensible and useful measuring 37 -- Conclusion 41 -- 3 The State's Measurements: The Construction and -- Use of Official Statistics 44 -- The history of statistics as measures 45 -- Official and semi-official statistics 49 -- Social indicators 52 -- Tracing individuals 56 -- Secondary data analysis 57 -- Sources 57 -- Conclusion 58 -- 4 Measuring the Complex World: The Character of Social Surveys 61 -- Knowledge production - the survey as process 63 -- Models from surveys - beyond the flowgraph? 66 -- Representative before random - sampling in the real world 72 -- Conclusion 77 -- 5 Probability and Quantitative Reasoning 79 -- Objective probability versus the science of clues 80 -- Single case probabilities - back to the specific 84 -- Gold standard - or dross? 84 -- Understanding Head Start 88 -- Probabilistic reasoning in relation to non-experimental data 90 -- Randomness, probability, significance and investigation 92 -- Conclusion 93 -- 6 Interpreting Measurements: Exploring, Describing and Classifying 95 -- Basic exploration and description 96 -- Making sets of categories - taxonomy as social exploration 99 -- Can classifying help us to sort out causal processes? 105 -- Conclusion 110 -- 7 Linear Modelling: Clues as to Causes 112 -- Statistical models 113 -- Flowgraphs: partial correlation and path analysis 116 -- Working with latent variables - making things out of things -- that don't exist anyhow 117 -- Multi-level models 120 -- Statistical black boxes - Markov chains as an example 122 -- Loglinear techniques - exploring for interaction 123 -- Conclusion 128 -- 8 Coping with Non-linearity and Emergence: Simulation and -- Neural Nets 130 -- Simulation - interpreting through virtual worlds 131 -- Micro-simulation - projecting on the basis of aggregation 133 -- Multi-agent models - interacting entities 135 -- Neural nets are not models but inductive empiricists 139 -- Models as icons, which are also tools 141 -- Using the tools 142 -- Conclusion 143 -- 9 Qualitative Modelling: Issues of Meaning and Cause 145 -- From analytic induction through grounded theory to computer -- modelling - qualitative exploration of cause 147 -- Coding qualitative materials 150 -- Qualitative Comparative Analysis (QCA) - a Boolean approach 154 -- Iconic modelling 157 -- Integrative method 159 -- Conclusion 160 -- Conclusion 162 -- Down with: 162 -- Up with: 163 -- Action theories imply action164. |
| Record Nr. | UNINA-9910782487003321 |
|
Byrne D. S (David S.), <1947->
|
||
| London, : SAGE, 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Interpreting quantitative data / / David Byrne
| Interpreting quantitative data / / David Byrne |
| Autore | Byrne D. S (David S.), <1947-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | London ; ; Thousand Oaks, Calif., : SAGE, 2002 |
| Descrizione fisica | 1 online resource (x, 176 p.) : ill |
| Disciplina | 300.72 |
| Soggetto topico |
Research
Methodology Social sciences - Statistical methods |
| ISBN |
9786611897642
9781446230282 1446230287 9781281897640 1281897647 9781849209311 1849209316 9781848608665 1848608667 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine generated contents note: Introduction 1 -- 1 Interpreting the Real and Describing the Complex: -- Why We Have to Measure 12 -- Positivism, realism and complexity 14 -- Naturalism - a soft foundationalist argument 17 -- There are no universals but, nevertheless, we can know 19 -- Models and measures: a first pass 21 -- Contingency and method - retroduction and retrodiction 25 -- Conclusion 27 -- 2 The Nature of Measurement: What We Measure and -- How We Measure 29 -- Death to the variable 29 -- State space 32 -- Classification 34 -- Sensible and useful measuring 37 -- Conclusion 41 -- 3 The State's Measurements: The Construction and -- Use of Official Statistics 44 -- The history of statistics as measures 45 -- Official and semi-official statistics 49 -- Social indicators 52 -- Tracing individuals 56 -- Secondary data analysis 57 -- Sources 57 -- Conclusion 58 -- 4 Measuring the Complex World: The Character of Social Surveys 61 -- Knowledge production - the survey as process 63 -- Models from surveys - beyond the flowgraph? 66 -- Representative before random - sampling in the real world 72 -- Conclusion 77 -- 5 Probability and Quantitative Reasoning 79 -- Objective probability versus the science of clues 80 -- Single case probabilities - back to the specific 84 -- Gold standard - or dross? 84 -- Understanding Head Start 88 -- Probabilistic reasoning in relation to non-experimental data 90 -- Randomness, probability, significance and investigation 92 -- Conclusion 93 -- 6 Interpreting Measurements: Exploring, Describing and Classifying 95 -- Basic exploration and description 96 -- Making sets of categories - taxonomy as social exploration 99 -- Can classifying help us to sort out causal processes? 105 -- Conclusion 110 -- 7 Linear Modelling: Clues as to Causes 112 -- Statistical models 113 -- Flowgraphs: partial correlation and path analysis 116 -- Working with latent variables - making things out of things -- that don't exist anyhow 117 -- Multi-level models 120 -- Statistical black boxes - Markov chains as an example 122 -- Loglinear techniques - exploring for interaction 123 -- Conclusion 128 -- 8 Coping with Non-linearity and Emergence: Simulation and -- Neural Nets 130 -- Simulation - interpreting through virtual worlds 131 -- Micro-simulation - projecting on the basis of aggregation 133 -- Multi-agent models - interacting entities 135 -- Neural nets are not models but inductive empiricists 139 -- Models as icons, which are also tools 141 -- Using the tools 142 -- Conclusion 143 -- 9 Qualitative Modelling: Issues of Meaning and Cause 145 -- From analytic induction through grounded theory to computer -- modelling - qualitative exploration of cause 147 -- Coding qualitative materials 150 -- Qualitative Comparative Analysis (QCA) - a Boolean approach 154 -- Iconic modelling 157 -- Integrative method 159 -- Conclusion 160 -- Conclusion 162 -- Down with: 162 -- Up with: 163 -- Action theories imply action164. |
| Record Nr. | UNINA-9910956129703321 |
|
Byrne D. S (David S.), <1947->
|
||
| London ; ; Thousand Oaks, Calif., : SAGE, 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||