Tag: data

• ∎ Data Science and Prediction - Dhar - 2013 - Reading Session 202301271312

  Last updated Jan 27, 2023 | Originally published Jan 27, 2023

  In situations where we are able to design randomized trials, big data makes it feasible to uncover the causal models generating the data.

  The author doesn’t make this point very big but it is actually quite important. There are many cases in which it is unethical to undertake a conventional scientific study of certain phenomena… Even though we know that those phenomena are happening anyway. If the data is collected “naturally,” however, we may be able to trace and track patterns in these data without putting ourselves in precarious ethical situations

  • Data
  • Research-Methods
  • Research

• Introducing Into the Dataverse, the article series

  Published Jan 23, 2020

  # README.txt: Introducing Into the Dataverse, the article series

  There is a significant gap in research about Canadian data collection activities on a granular scale. This lack of knowledge regarding data collection practices within Canada hinders the ability of policymakers, civil society organizations, and the private sector to respond appropriately to the challenges and harness unrealized benefits.

  So true. This looks like an interesting series from the great team at Brookfield.

  • Highlights
  • Data
  • Tech
  • Change

• The Tyranny of Categorization

  Published Jan 23, 2020

  Herein, then, lies the tyranny of classification: The borders we draw for ourselves create a prison of thought and collaboration, inhibiting movement, connectivity, and learning.

  Dominic Hofstetter outlines the many benefits of categorization, too. We have to have both specialization and generalization—categories and loose files. The key is developing processes, protocols, and ways of working that elevate the benefits of both.

  • Highlights
  • Data