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Summary

Longue durée analysis employs descriptive statistics and data visualization of explore univariate, bivariate, and multivariate trends. These trends tracks historical historical changes in a thinner manner than eventful analysis, but in return they explore such trends over longer time periods and larger numbers of cases. It introduces four graph types: serial scatterplots, contextualized line graphs, developmental typologies, and serial bar graphs that are used to visualize trends. Longue durée analysis frequently redescribes mi-described trends by paying close attention to three sources of misdescription: inadequate baselining, unfreezing of time scales, and mismeasurements. It discusses how using stock instead of flow indicators increases the ability of time series to capture historical changes.

My fellow contractarians and I are of a mind that it would be irrational to comply with a distribution of the cooperative dividend that worsens one’s condition. But worse than what? According to David Gauthier et al., it’s non-interaction, i.e., what would be the case were the negotiators never to have met. I argue that it’s what would be the case in the absence of their coming to an agreement. As it turns out, this distinction can be, and often is, a matter of life and death.

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6 - Longue Durée Analysis

Summary

Getting the Baseline Right—or—Why I’m Right and Everyone Else is Wrong, in each of the Two Senses of ‘Why’

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2 results

6 - Longue Durée Analysis

Summary

Getting the Baseline Right—or—Why I’m Right and Everyone Else is Wrong, in each of the Two Senses of ‘Why’