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Rewards Analytics and Distribution Dashboard for Quantification Review¶

This document processes the outputs of the praise reward system and performs an analysis of the resulting token reward distribution.

Out[6]:

Distribution report for round-34

  • This period covers praise given between 2023-07-24 and 2023-08-21.
  • We allocated a total of 512.9778481012659 TEC tokens for rewards.
  • Duplicate praise received a weighting of 0.1 the value of the original praise.
  • We assigned 3 quantifiers per praise instance.
  • Praise receiver names were not hidden behind pseudonyms during quantification

Praise Data Visualization¶

Rating 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.

Top 10 highest rated contributions¶

The ten highest rated contributions for this round were the following:

Out[9]:
Avg. score To Reason
57.6666666666667 akrtws#4246 for all their hard work on planning and executing on TE Barcamp!
41.0 liviade#1387 for her excellent presentation at EthCC on the results of the TE stakeholder study!
38.3333333333333 akrtws#4246 for their great presentations at ETHCC and the TEBarcamp
36.6666666666667 0xr3x for their great presentations at ETHCC and the TEBarcamp
34.0 pat.zip (TE Academy)#5266 for all their hard work on planning and executing on TE Barcamp!
29.6666666666667 gideonro#0 For dedicate leadership at TEC during the transition over the past two years.
29.6666666666667 Tamarandom#9361 for their great presentations at ETHCC and the TEBarcamp
25.3333333333333 roro#1166 for his work with the TE AI and his insightful presentations about it at ETHCC and the Barcamp
22.6666666666667 pat.zip (TE Academy)#5266 For their devotion to the TE academy and pioneering the domain of decentralized education and Token Engineering education.
22.6666666666667 Isaac (enti)#1546 for representing the TEC and presenting on TE at a major crypto conference! Awesome work!

Praise Reward Distribution¶

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.

Praise Giving Distribution¶

We can also take a look at the amount of praise different users gave.

Praise Flows¶

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.

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Quantifier Data¶

Now let's take a closer look at the quantification process and the quantifiers:

Praise Outliers¶

To aid the revision process, we highlight disagreements between quantifiers.

Outliers sort by spreads¶

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" .

Praise score by quantifier -- outliers among the quantifiers?¶

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.

Score displacement: tendency to under/over-scoring?¶

Scoring correlation: how similiar am I scoring with others?¶

Agreement on duplication¶

Out[22]:

Among 173 praises, 45 (26.01%) 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'.

Agreement on dismissal¶

Out[25]:

Among 173 praises, 0 (0.00%) 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.