3.4 KiB
GiveWell
wget --recursive --no-clobber --html-extension --domains givewell.org --follow-tags=a --reject '.js,.css,.ico,.txt,.gif,.jpg,.jpeg,.png,.mp3,.mp4,.pdf,.tgz,.flv,.avi,.mpeg,.iso,.xls,.xlsx,.csv,.doc,.docx,.mpa,*mp4' --ignore-tags=img,link,script --header="Accept: text/html" --no-parent https://www.givewell.org
grep -ri "Internal forecast" -E "prediction|Prediction|forecast|Forecast" * | sed 's/^/https://www.givewell.org//' > searchresults.txt
grep -ril "Internal forecast" -E "prediction|Prediction|forecast|Forecast" * > searchresults.txt cat searchresults.txt cat searchresults.txt | sed 's/^/https://www.givewell.org//' > searchresults2.txt cat searchresults2.txt grep -v "print" searchresults2.txt > searchresults3.txt
while read line; do firefox --new-tab "$line" done < searchresults3.txt
We are experimenting with recording explicit numerical forecasts of the probability of events related to our decision-making (especially grant-making). The idea behind this is to pull out the implicit predictions that are playing a role in our decisions, and to make it possible for us to look back on how well-calibrated and accurate those predictions were.
For this grant, we are recording the following forecasts For this grant, we are recording the following forecasts: For this grant, we are recording the following forecast: For this grant, we are recording the following forecasts (made during our decision process):
We are experimenting with recording explicit numerical forecasts of the probability of events related to our decision-making (especially grant-making). The idea behind this is to pull out the implicit predictions that are playing a role in our decisions, and to make it possible for us to look back on how well-calibrated and accurate those predictions were. For this grant, we are recording the following forecast:
We’re experimenting with recording explicit numerical forecasts of events related to our decisionmaking (especially grantmaking). The idea behind this is to pull out the implicit predictions that are playing a role in our decisions, and make it possible for us to look back on how well-calibrated and accurate those are. For this grant, we are recording the following forecasts:
We’re experimenting with recording explicit numerical forecasts of events related to our decisionmaking (especially grantmaking). The idea behind this is to pull out the implicit predictions that are playing a role in our decisions, and make it possible for us to look back on how well-calibrated and accurate those are.
Divide by h2, then pull the second which has forecasts
OpenPhil
wget --recursive --no-clobber --html-extension --domains www.openphilanthropy.org --follow-tags=a --reject '.js,.css,.ico,.txt,.gif,.jpg,.jpeg,.png,.mp3,.mp4,.pdf,.tgz,.flv,.avi,.mpeg,.iso,.xls,.xlsx,.csv,.doc,.docx,.mpa,*mp4' --ignore-tags=img,link,script --header="Accept: text/html" --no-parent https://www.openphilanthropy.org
Find and delete largest files du -a . | sort -n -r | head -n 20 find . -xdev -type f -size +100M
find . -type f -exec du -s {} ; | sort -r -k1,1n | head -n 20
grep -ril -E "Internal forecast" * > searchresults.txt
grep -v "print" searchresults.txt > searchresults2.txt
Note to self: OpenPhil uses h3 headers instead.