CE has rating that include wild fish and wild fish caught for human use.
Thank you for the relevant questions.
Is this only from the animal products the child would have eaten themself? Should the consumption from that child’s descendants be included?
Yes, in our preliminary analysis we only include effects in the first generation, adjusted for the possible increase in consumption by other family members due to increased income. We will analyse the impact of prevented consumption in the next generation, but give it smaller weight than direct effect in the first birth averted.
FWIW, TLYCS recommends PSI and DMI, and DMI is one of GiveWell’s standout charities, and both do family planning work.
We are aligned more with GiveWell’s methodology and consider their recommendations more representative. Family planning is one of many interventions DMI does with considerably less resources spent on it compare to other interventions.
What is even more important, DMI (and PSI) don’t work with impact on animal welfare in mind. That leads to choice of countries (Burkina Faso, DRC, Mozambique) that are one of the least promising form the perspective of their effect on animals (we have a report on priority countries coming out soon).
We are very skeptical about being able to make any progress on far future effects of population given the time cap we put on this report and our general skepticism towards being able to make accurate far future predictions. We use something closest to a “weighted quantitative model” but would only do a more explicit model of this for the top charity ideas we investigate deeper.
Broadly we have not considered WAS due to separate reports/views on how to deal with that (coming out soon). In short, epistemically, we tend to take a cluster view, one of which would be a cluster concerned with flow through effects. We think wild animal suffering will often be the most important consideration within flow through effects and we expect flow through effects to carry between 1% and 25% of our endline evaluation of the intervention’s promisingness. Overall, we think the effects other interventions have on wild animal suffering should be considered as a non-trivial factor, but not a dominating one. We will analyze it thoroughly in the next stage of research if this intervention would make to top 3 after shallow research of all asks we consider.
1) As you correctly observed, we didn’t adjust welfare points for population size and odds of feeling pain in this spreadsheet. But we just publish another report summarizing our animal prioritization research where we aggregated information about baseline welfare points, population size, odds of feeling pain, neglectedness, and amount of suffering caused by a smaller number of specific reasons.Generally, when we are calculating the cost-effectiveness of a given intervention we take into account the number of welfare points “gained” (baseline welfare points changed counterfactually by the intervention) multiplied by odds of feeling pain and number of animals affected.We also need to adjust for length of life. For example, if the baseline welfare points per year for a cow is −20 and for broiler chicken is −56, but beef cow spends 402 days on a farm, their WP would be multiplied by the percentage of year they spend on the farm, so 402 days / 365 days in a year = 110%, and broiler chicken spend 42 days, then WPs would be multiplied by 12% resulting in:Cow: −22 welfare points per lifetime of an individualBroiler chicken: −6.72 welfare points per lifetime of an individual.2) The range is the minimum and maximum values of welfare points as rated by our external reviewers. “Total welfare score” (second column) is an average of internal and external reviewer’s ratings.
Please link to the examples here when they are finished, thanks!
We had applied this system to 15 different animals/breeds and recently posted the summary of our research here.
Some examples of this model being applied would be very helpful for understanding the model.
We pulled the data on odds of feeling pain from Open Phil’s report on consciousness and moral patienthood. The probability of consciousness (as loosely defines by examples in the report) for a given species were estimated based on proxies like last common ancestor with humans, neurobiological features, nociceptive features and other behavioral/cognitive features. In our system, we based weighting of different criteria based on multiple factors including proxying ethical value accuracy (metric and ethical value, encapsulation, directness and gamability) and cross-applicability, including cross-animal applicability. You can read more on that in our previous post.
Some farms (e.g. GAP farms) do have better nutritional practices, although there is not great specific data from them. That being said, there is other evidence that both calcium has an impact and theoretical reasons why a large number of farms would not supplement well. Farms do experiment with food a lot but not generally with welfare in mind. It’s not currently an issue at the front of consumers’ minds.
One of the requirements for Global Animal Partnership (GAP) certified farms is “Hens must be provided with sufficient calcium in their diet to maintain hen’s health and eggshell quality.” There are approximately 20 chicken farms signed up to this program and they might provide an adequate level of calcium. Welfare of hens is measured individually for every farm, but according to my knowledge, they are not conducting any studies. Fortunately, evidence base for calcium and phosphorus supplementation is pretty strong. For example, according to this analysis for hens at age 462-543 days of life increasing dietary calcium
from 24-25 to 36-40 g/kg decreased mortality by 5.5% (22.8% → 17.3%) and improved egg production, shell weight (SW) and shell thickness (ST)
from 36-40 g/kg to 49 g/kg by next 5.4% (17.3% − 11.9%) but did not affect egg production but increased SW and/or ST.
Farmers do prepare their own fortified feed premixes, but it is unlikely that they provide an adequate level of nutrients because the currently recommended dosage is not optimal. One study compared turkey’s health benefits of currently recommended by National Research Council (NRC) dosage of phosphorus and diets that were 0.06% higher than NRC recommended levels; 0.1% higher than the medium diet, and 0.1% higher than the high diet.In addition to lower body weights, turkeys fed with the NRC recommended diet had higher incidences of bone fractures and reduced the walking ability, indicating that feeding nonphytate phosphorus at levels above NRC recommended levels resulted in improved growth and better skeletal integrity compared to NRC recommended levels. Similarly, the level of calcium can affect skeletal properties and body weight. For example, Tatara et al. (2011) reported improved skeletal properties and increased body weights in turkeys provided with 95% or more of NRC recommended calcium compared to those provided with 85% of NRC recommended calcium. (source, page 281)
Additionally given that economically, phosphorus is the third most expensive component in a non-ruminant diet after energy and protein, it is less likely that chickens in the standard farm have an adequate level of this mineral. One of the biggest feed distributors, DSM, that additionally seems to focus on animal welfare outside of the profitability of having healthy animals, supplement feed with vitamins, but not dietary minerals like calcium.
The evidence is strong enough to research this, ask more deeply, and we are planning to conduct more research to determine the exact level of nutrients in chicken’s diet and evaluate the change in welfare points cause by fortification. Interestingly, feed (as well as chickens) is often provided to the farmers by large food companies (e.g. Tyson Foods who contract out the raising of the birds to the farmers, so we will compare the level of nutrients added by Tyson Food to the optimal dosage to determine if the ask is still more cost-effective than other interventions we are investigating.
Thank you, Joey, for gathering those data. And thank you, Darius, for providing us with the suggestions for reducing this risk. I agree that further research on causes of value drift and how to avoid it is needed. If the phenomenon is explained correctly, that could be a great asset to the EA community building. But regardless of this explanation, your suggestions are valuable.
It seems to be a generally complex problem because retention encapsulates the phenomenon in which a person develops an identity, skill set, and consistent motivation or dedication to significantly change the course of their life. CEA in their recent model of community building framed it as resources, dedication, and realization.
Decreasing retention is also observed in many social movements. Some insights about how it happens can be culled from sociological literature. Although it is still underexplored and the sociological analysis might have mediocre quality, but it might still be useful to have a look at it. For example, this analysis implicate that “movement’s ability to sustain itself is a deeply interactive question predicted by its relationship to its participants: their availability, their relationships to others, and the organization’s capacity to make them feel empowered, obligated, and invested.”
Additional aspects of value drift to consider on an individual level that might not be relevant to other social movements: mental health and well-being, pathological altruism, purchasing fuzzies and utilons separately.
The reasons for the value drift from EA seems to be as important in understanding the process, as the value drift that led to EA, e.g. In Joey’s post, he gave an illustrative story of Alice. What could explain her value drift was the fact that at people during their first year of college are more prone to social pressure and need for belonging. That could make her become EA and drifted when she left college and her EA peers. So “Surround yourself with value aligned people” for the whole course of your life. That also stresses the importance of untapped potential of local groups outside the main EA hubs. For this reason, it’s worth considering even If in case of outreach we shouldn’t rush to translate effective altruism
About the data itself. We might be making wrong inferences trying to explain those date. Because it shows only a fraction of the process and maybe if we would observe the curve of engagement it would fluctuate over a longer period of time, eg. 50% in the first 2-5 year, 10% in a 6th year, 1% in for the next 2-3 and then coming back to 10%, 50% etc.? Me might hypothesize that life situation influence the baseline engagement for short period (1 month- 3 years). As analogous for changes in a baseline of happiness and influences of live events explained by hedonic adaptation, maybe we have sth like altruistic adaptation, that changes after a significant live event (changing the city, marriage etc.) and then comes back to baseline.
Additionally, the level of engagement in EA and other significant variables does not correlate perfectly, the data could also be explained by the regression to the mean. If some of the EAs were hardcore at the beginning, they will tend to be closer to the average on a second measurement, so from 50% to 10%, and those from 10% to 1%. Anyhow, the likelihood that the value drift is true is higher than that it’s not.
More could be done about the vale drift on the structural level, e.g. it might be also explained by the main bottlenecks in the community itself, like the Mid-Tire Trap (e.g. too good for running local group, but no good enough to be hired by main EA organizations → multiple unsuccessful job applications → frustration → drop out).
Becuase mechanism of the value drift would determine the strategies to minimalize risk or harm of it and because the EA community might not be representative for other social movements, we should systematically and empirically explore those and other factors in order to find the 80⁄20 of long-lasting commitment.