[nltk_data] Downloading package stopwords to /root/nltk_data... [nltk_data] Unzipping corpora/stopwords.zip.
This document processes the outputs of the praise reward system and performs an analysis of the resulting token reward distribution.
Since praise gets valued on a scale, we can take a look at how often each value of the scale gets assigned by quantifiers. Note: This metric disregards scores of praise marked as a duplicate, since the score of the original is already being taken into account.
The ten highest rated contributions for this round were the following:
| Avg. score | To | Reason |
|---|---|---|
| 32.75 | r-x-x#8344 | for thinking deeply about how to reorganize our Discord to be easier to navigate and beign more aligned to the direction of the org transformation. You've put so much effort into this and it shows. |
| 29.5 | acidlazzer#5796 | for managing the TEC's first Twitter Space Community Call. This is a great first step toward shifting these calls to be more externally oriented and focused on the topics of token engineering |
| 27.07 | r-x-x#8344 | for rolling up the sleeves and doing some long overdue cleanup amongs passwords, authentication tokens, admin roles etc.. ! |
| 27.0 | kristofer#1475 | for being a genius! An absolute genius. But I can't say why yet. |
| 26.75 | durgadas#9280 | for his courage coming forward and delivering a complex course to a group of unknown folks, and being in control enough to answer questions and stick to the plan and timescales |
| 26.25 | eduardovegap#0422 | for doing a great job of facilitating the TEC's first Twitter Space Community Call. A total natural and a nice way to continue to have your presence felt in the community! |
| 25.5 | solsista#5370 | for holding to the Consilience Library vision and working on its implementation, You right @solsista 🤩 |
| 25.5 | BiancaGadelha#2667 | for steering the immediate needs of Gravity, allowing Juan to step back a bit to take some time thinking through next steps for Gravity. Yay Bianca! |
| 24.25 | Juankbell#7458 | for their leadership outreach for grants for Gravity |
| 24.25 | liviade#1387 | for representing the TEC at the Doingud twitter space <3 |
We can now take a look at the distribution of the received praise rewards. You can toggle the inclusion of the different sources by clicking on the legend.
We can also take a look at the amount of praise different users gave.
Now for something more fun: let's surface the top "praise flows" from the data. Thanks to @inventandchill for this awesome visualization! On one side we have the top 15 praise givers separately, on the other the top 25 receivers. The people outside the selection get aggregated into the "REST FROM" and "REST TO" categories.
Now let's take a closer look at the quantification process and the quantifiers:
To aid the revision process, we highlight disagreements between quantifiers.
This graphic visualizes controversial praise ratings by sorting them by the "spread" between the highest and lowest received score.
Please keep in mind that this is a visual aid. If there are several praise instances with similar spread and quant score, all but one end up "hidden" on the chart. For an exhaustive list, take a look at the exported file "praise_outliers.csv" .
Let's see how different quantifiers behaved by showing the range of praise scores they gave.
To interpret the box plot:
Bottom horizontal line of box plot is minimum value
First horizontal line of rectangle shape of box plot is First quartile or 25%
Second horizontal line of rectangle shape of box plot is Second quartile or 50% or median.
Third horizontal line of rectangle shape of box plot is third quartile or 75%
Top horizontal line of rectangle shape of box plot is maximum value.
Among 62 praises, 2 (3.23%) do not agree on duplication
Praise instances with disagreements in duplication are collected in 'results/duplication_examination.csv'. To compare, look at the last 4 columns: 'DUPLICATE MSG 1/2/3' and 'ORIGINAL MSG'.
Among 62 praises, 1 (1.61%) do not agree on dismissal
Praise instances with disagreements in dismissal are collected in'results/dismissal_disaggreed.csv'. You can further look into who dismissed and who did not.