Better World Shopper (https://betterworldshopper.org/) is an effort worth checking out. It attempts to score companies in various domains along a number of ethics-related axes ("human rights", "the environment", "animal protection", "community involvement", "social justice")
It has some major limitations and is certain to be incomplete/inaccurate in many ways (I think it is basically the result of one person's PhD work and a continuation of that effort afterwards), but, it's still a great starting point to at least understand the broad strokes of which companies have the best/worst track records, and I think something similar scaled up and with a more transparent code/database could do a lot of good in helping to keep track of how organizations are behaving over longer the long run.
If you look at the other articles published by the author, Deena Shanker, they are pretty much all doom-and-gloom headlines related to plant-based companies:
If it's a topic you are interested in, I would definitely recommend checking out the original article to decide for yourself.
Basically though, the authors looked at a bunch of different measures relating to "poor outcome" at age 35: Alcohol use, smoking, illicit drug use, relationship status, financial hardship, depression, anxiety and employment status.
Of those, the only significant associations they found were with high-risk alcohol use, likelihood to have used other illicit drugs (with the implicit assumption that this is a bad thing), daily cigarette smoking, and lack of relationship.
From the abstract:
"By the mid‐30s, both young‐adult and adolescent‐onset regular users were more likely than minimal/non‐users (63.5%) to have used other illicit drugs (odds ratio [OR] > 20.4), be a high‐risk alcohol drinker (OR > 3.7), smoked daily (OR > 7.2) and less likely to be in relationships (OR < 0.4)."
Excessive drinking and daily smoking are both pretty negative things, imo, but they are only showing a correlation, and that not surprising at all. People use all three substances to cope. The (small-ish) relationship association found is also interesting and could be viewed as a negative, but this too is just a correlation.
Relating to the other negative outcomes like depression and anxiety, the authors find:
"The distribution of having a paid job, anxiety, depression and financial hardship were similar to the percentage of each class in the population."
Cool.
It would be nice if in 2021 we could start being a bit more objective about how we approach studying substance use.
There are real risks and harms associated with cannabis use, some of which we understand, and others we likely don't fully appreciate due to a lack of studies.
Overstating things to further some agenda or to support one's subjective preconceptions helps no one and only serves to further dilute our actual understanding of the science, and is ultimately going to do more harm than good.
Very cool! Couple thoughts -
1. I noticed some artists get added a second time as the network expands, so some de-duplication may be needed?
2. It could be interesting to (optionally) scale the node size or border width with respect to the node degree.. In particular for the nodes that were clicked on (and thus, have their degrees inflated).. this way it would be easy to spot artists that have a lot of connections just based on who else is currently displayed.
1. I noticed some artists get added multiple times, so some deduplication may be needed.
2. Perhaps you could (optionally) scale the node sizes or border widths with their degrees?
It has some major limitations and is certain to be incomplete/inaccurate in many ways (I think it is basically the result of one person's PhD work and a continuation of that effort afterwards), but, it's still a great starting point to at least understand the broad strokes of which companies have the best/worst track records, and I think something similar scaled up and with a more transparent code/database could do a lot of good in helping to keep track of how organizations are behaving over longer the long run.