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Geisteswissenschaften
This is a term that came into common use in the 19th century, referring to the humanities and social sciences. In the context of methodology, it also implies a particular approach to work in these fields, one that emphasizes the role of VERSTEHEN.
There were isolated uses of Geisteswissenschaften, or its variants, before 1849, but widespread employment of the term seems to have stemmed from Schiel's translation into German of John Stuart Mill's System of Logic (Mill, 1974), in which the term Geisteswissenschaften was used to stand for Mill's “moral sciences.” Mill regarded psychology as the key moral science, and its method was to be modeled on the natural sciences (Naturwissenschaften). However, most of the German historians and philosophers who adopted the term Geisteswissenschaften took a very different view. Some earlier German writers, notably Goethe and Hegel, had sought to develop a notion of scientific understanding that encompassed not just natural science but also the humanities and philosophy, thereby opposing empiricist and materialist views of scientific method and their extension to the study of human social life. However, by the middle of the 19th century, attempts at such a single, comprehensive view of scholarship had been largely discredited in many quarters. Instead, influential philosophers argued that the human social world had to be studied in a quite different way from the manner in which natural scientists investigate the physical world, although one that had equal empirical rigor. As a result, it is common to find Geisteswissenschaften translated back into English as “the human studies” or “the human sciences,” signaling distance from the positivist view of social research marked by labels such as behavioral science.
One of the most influential accounts of the distinctiveness of the Geisteswissenschaften is found in the work of Wilhelm Dilthey (see Ermarth, 1978). He argued that whereas the natural sciences properly approach the study of phenomena from the outside, by studying their external characteristics and behavior, we are able to understand human beings and their products—whether artifacts, beliefs, ways of life, or whatever—from the inside because we share a common human nature with those we study. Another influential 19th-century account of the distinctiveness of the human sciences was put forward by the neo-Kantians Windelband and Rickert. For them, the distinction between the natural and social sciences was not primarily about subject matter; indeed, the neo-Kantians were keen to emphasize that there is only one reality (see Hammersley, 1989, pp. 28–33). Rather, the main difference was between a generalizing and an individualizing form of science. Max Weber drew on both the Diltheyan and neo-Kantian traditions in developing his verstehende sociology, in which explanation (Erklären) and understanding (Verstehen) go together, so that any sociological account is required to be adequate at the level of both cause and meaning (Turner & Factor, 1981).
References
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- Analysis of Variance
- Association and Correlation
- Association
- Association Model
- Asymmetric Measures
- Biserial Correlation
- Canonical Correlation Analysis
- Correlation
- Correspondence Analysis
- Intraclass Correlation
- Multiple Correlation
- Part Correlation
- Partial Correlation
- Pearson's Correlation Coefficient
- Semipartial Correlation
- Simple Correlation (Regression)
- Spearman Correlation Coefficient
- Strength of Association
- Symmetric Measures
- Basic Qualitative Research
- Basic Statistics
- F Ratio
- N(n)
- t-Test
- X¯
- Y Variable
- z-Test
- Alternative Hypothesis
- Average
- Bar Graph
- Bell-Shaped Curve
- Bimodal
- Case
- Causal Modeling
- Cell
- Covariance
- Cumulative Frequency Polygon
- Data
- Dependent Variable
- Dispersion
- Exploratory Data Analysis
- Frequency Distribution
- Histogram
- Hypothesis
- Independent Variable
- Measures of Central Tendency
- Median
- Null Hypothesis
- Pie Chart
- Regression
- Standard Deviation
- Statistic
- Causal Modeling
- Discourse/Conversation Analysis
- Econometrics
- Epistemology
- Ethnography
- Evaluation
- Event History Analysis
- Experimental Design
- Factor Analysis and Related Techniques
- Feminist Methodology
- Generalized Linear Models
- Historical/Comparative
- Interviewing in Qualitative Research
- Latent Variable Model
- Life History/Biography
- Log-Linear Models (Categorical Dependent Variables)
- Longitudinal Analysis
- Mathematics and Formal Models
- Measurement Level
- Measurement Testing and Classification
- Multilevel Analysis
- Multiple Regression
- Qualitative Data Analysis
- Sampling in Qualitative Research
- Sampling in Surveys
- Scaling
- Significance Testing
- Simple Regression
- Survey Design
- Time Series
- ARIMA
- Box-Jenkins Modeling
- Cointegration
- Detrending
- Durbin-Watson Statistic
- Error Correction Models
- Forecasting
- Granger Causality
- Interrupted Time-Series Design
- Intervention Analysis
- Lag Structure
- Moving Average
- Periodicity
- Serial Correlation
- Spectral Analysis
- Time-Series Cross-Section (TSCS) Models
- Time-Series Data (Analysis/Design)
- Trend Analysis
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