
Sign up to save your podcasts
Or


A Canadian scientist wanted to demonstrate how he could use DNA barcoding to distinguish between different strains of cannabis; a pretty valuable thing to be able to do during the weed marketing gold rush.
To prove it, he just took a graph of U.S. arrest data, changed the title, and said 'here, here's my evidence.'
He did a lot more than that. And it might have all gone unnoticed, if not for some meddlesome researchers. Senior producer Sarah Lawrynuik gets into it.
Featured in this episode: Charles Piller, investigative journalist for Science Magazine; Ken Thompson, post-doctoral fellow at Stanford University; Paul Hebert, director of the University of Guelph's Centre for Biodiversity Genomics
Further reading:
Support Canadaland at canadaland.com/join
Sponsors: oxio, Shopify, Article
Additional Music is by Audio Network
Support CANADALAND: https://canadaland.com/join
See omnystudio.com/listener for privacy information.
Hosted on Acast. See acast.com/privacy for more information.
By CANADALAND4
150150 ratings
A Canadian scientist wanted to demonstrate how he could use DNA barcoding to distinguish between different strains of cannabis; a pretty valuable thing to be able to do during the weed marketing gold rush.
To prove it, he just took a graph of U.S. arrest data, changed the title, and said 'here, here's my evidence.'
He did a lot more than that. And it might have all gone unnoticed, if not for some meddlesome researchers. Senior producer Sarah Lawrynuik gets into it.
Featured in this episode: Charles Piller, investigative journalist for Science Magazine; Ken Thompson, post-doctoral fellow at Stanford University; Paul Hebert, director of the University of Guelph's Centre for Biodiversity Genomics
Further reading:
Support Canadaland at canadaland.com/join
Sponsors: oxio, Shopify, Article
Additional Music is by Audio Network
Support CANADALAND: https://canadaland.com/join
See omnystudio.com/listener for privacy information.
Hosted on Acast. See acast.com/privacy for more information.

393 Listeners

151 Listeners

236 Listeners

207 Listeners

77 Listeners

69 Listeners

112 Listeners

24 Listeners

87 Listeners

9 Listeners

1,590 Listeners

458 Listeners

46 Listeners

27 Listeners

273 Listeners

116 Listeners

43 Listeners

3 Listeners