I love the set of summaries in the main report, as well as the color-coding. Iâve suddenly learned a lot more about a topic that really interests meâthanks for posting!
However, Iâm confused about the step where all of these color-coded possibilities turn into a chart with probability distributions, and I wish I could learn more about the Guesstimate model.
In particular, seeing reviewersâ comments on individual cells would be greatâwhy did two different people estimate that âprobability that all companies defect in a Prisonerâs Dilemma scenarioâ was ~100 times as meaningful a consideration as âwhat. ACE thinks makes an effective campaignâ?
It also took me a while to parse how the âqualitative updateâ figure meshed with the âquantitative updateâ figure to create the final 0.44 number.
One other specific question (which stands in for several I had reading the model): Why are farmersâ opinions about the industry weighted equally with observed evidence about what companies are actually doing? I can see the appeal of evenly weighting all major factors for simplicity, but in general I like to rely on observed evidence much more than opinion surveys, and I would assume CE has the same preference. (I may be misunderstanding something about the model, though!)
When it comes to the step between research questions and the probability distribution, full research, answering each question, can be seen in the full report. In the report, we also address some of the concerns you have with the judgement calls on each of the âqualitativeâ parameters.
Each update incorporates the weight we put on this factor, the directionality and strength. Those factors, again, rely on other information. With the example, you cited âwhat ACE thinks makes an effective campaignâ vs âprobability that all companies defect in a Prisonerâs Dilemma scenarioâ. For example, ACEâs opinion on the importance of public support when launching corporate campaigns is formed based on the intervention report they have researched in November 2014, and as they currently claim âis not up to our current standards.â. The landscape has changed since then. As of recent, we can observe that there is a strong track record of successful corporate campaigns in countries where the society didnât have sympathetic views toward animals (e.g. Lithuania or Japan). I think we can rely more and more on rigorous and generalizable conclusions from research on real-life examples and on the application of game theory to predict the behaviour of the companies.
I agree I wish we had enough time to flesh out the reasoning for each of the factors. Sadly, due to limited time we are constantly having to make trade-offs about whether we should put time into explaining the reasoning more deeply to the broader community vs discussing with the CE candidates vs researching more to get a deeper internal understanding. We generally plan on going deeply into these factors with the specific entrepreneurs looking to start this project or others, who are going to work/âare working in the field in the near term, but not publish much more on the topic publicly after our full report.
I love the set of summaries in the main report, as well as the color-coding. Iâve suddenly learned a lot more about a topic that really interests meâthanks for posting!
However, Iâm confused about the step where all of these color-coded possibilities turn into a chart with probability distributions, and I wish I could learn more about the Guesstimate model.
In particular, seeing reviewersâ comments on individual cells would be greatâwhy did two different people estimate that âprobability that all companies defect in a Prisonerâs Dilemma scenarioâ was ~100 times as meaningful a consideration as âwhat. ACE thinks makes an effective campaignâ?
It also took me a while to parse how the âqualitative updateâ figure meshed with the âquantitative updateâ figure to create the final 0.44 number.
One other specific question (which stands in for several I had reading the model): Why are farmersâ opinions about the industry weighted equally with observed evidence about what companies are actually doing? I can see the appeal of evenly weighting all major factors for simplicity, but in general I like to rely on observed evidence much more than opinion surveys, and I would assume CE has the same preference. (I may be misunderstanding something about the model, though!)
When it comes to the step between research questions and the probability distribution, full research, answering each question, can be seen in the full report. In the report, we also address some of the concerns you have with the judgement calls on each of the âqualitativeâ parameters.
Each update incorporates the weight we put on this factor, the directionality and strength. Those factors, again, rely on other information. With the example, you cited âwhat ACE thinks makes an effective campaignâ vs âprobability that all companies defect in a Prisonerâs Dilemma scenarioâ. For example, ACEâs opinion on the importance of public support when launching corporate campaigns is formed based on the intervention report they have researched in November 2014, and as they currently claim âis not up to our current standards.â. The landscape has changed since then. As of recent, we can observe that there is a strong track record of successful corporate campaigns in countries where the society didnât have sympathetic views toward animals (e.g. Lithuania or Japan). I think we can rely more and more on rigorous and generalizable conclusions from research on real-life examples and on the application of game theory to predict the behaviour of the companies.
I agree I wish we had enough time to flesh out the reasoning for each of the factors. Sadly, due to limited time we are constantly having to make trade-offs about whether we should put time into explaining the reasoning more deeply to the broader community vs discussing with the CE candidates vs researching more to get a deeper internal understanding. We generally plan on going deeply into these factors with the specific entrepreneurs looking to start this project or others, who are going to work/âare working in the field in the near term, but not publish much more on the topic publicly after our full report.