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From YouTube: W35 Softgov WG: Praise analysis and possible solutions
Description
TheSoftgov Working Group researches and applies best practices for governance, social collaboration and contribution rewards while implementing Ostrom’s 8 principles for governing the commons in its foundation.
We gather every Tuesday at 7pm CET.
Steward: Liviade
Timecodes:
00:00 - Agenda
07:01 - YGG intervetion Dashboard
21:48 - Octoupus analysis
30:20 xx - IH for each category
38:47 - Decision making process and the problem set
46:47 - Round of sharing solutions
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A
C
A
Cool
yeah,
I
thought
I
edited
already
well
that's
great.
Thank
you!
So
yeah
just
going
over
a
little
bit
of
what
we're
going
to
be
doing
today
and
then
I'll
pass
to
sean
to
get
us
started.
So
we'll
have
a
sharing
about
the
praise,
analysis,
tools
and
findings.
So
what
was
all
the
process
like
and
what
were
what
are
some
of
the
findings
that
we
have
to
make
informed
proposals
now
and
then
I'm
going
to
explain
what
is
the
decision
making
process
that
we
came
came
up
with
that?
D
Hey
everyone
yep,
so
what
I
want
to
show
off
is
deployed
online.
We
have
two
apps,
I'm
super
glad
octopus
just
jumped
in
here
octopus
and
I
have
been
putting
in
a
lot
of
work
on
this
over
the
past
six
weeks
or
so
it's
been
a
joy.
I
think
the
results
have
gone
beyond.
Certainly
beyond
my
expectations,
I
think
beyond
most
expectations
expectations.
It
was
really
nice
to
see
some
very
strong
data.
Scientists
come
together.
Octopus
and
muhammad
have
been
incredible,
like
I
think,
we're
all
we've.
D
D
That
being
said,
there's
so
much
happening
these
days
that
octopus
and
I
haven't
really
had
a
chance
to
sync
up
the
last
few
days.
So
I
think
we
both
have
some
results,
and
so
maybe
I'll
just
open
the
floor
for
a
few
minutes
to
get
started,
to
welcome
octopus
and
and
we'll
take
a
few
minutes
to
sort
of
live
coordinate
here
on
the
spot.
D
I'm
gonna
go
over
some,
the
interventions,
the
ubi
interventions
and
the
wage
deduction
intervention,
particularly
and
then
there's
also
a
really
cool
clustering
dashboard
that
muhammad
has
put
together,
and
he
also
did
the
work
on
the
praise
bucketing.
So
I
don't
think
that's
necessarily
been
deployed,
but
I
think
we
can
just
bring
up
the
chart
the
the
bar
plot
of
the
categories
and
talk
about
that
a
little
bit.
E
Yeah,
I
think
the
main
things
that
I
ended
up
figuring
out
were
the
the
different
measures
of
decentralization
and
thanks
to
griff
and
zeptimus.
I
think
I
I
was
able
to
get
some
good
information
about
comparing
these
things
to
different
other
crypto
projects,
so
rather
than
like,
comparing
them
to
switzerland
or
something,
and
I
think
that
that
helped
me
understand
more
context
for
the
different
metrics.
E
E
E
Especially
muhammad
was
working
with
the
label
data
and
using
the
hand,
labels
which
were
more
accurate,
and
I
was
using
sort
of
a
coarser
approach
that
just
tried
to
catch
retweets
and
meetings
based
on
what
I
thought
they
might
look
like.
So
our
where
we're
getting
our
numbers
from
is
a
little
bit
different,
but
the
numbers
ended
up
looking
similar.
So
it
was
a
confirmation
that
they're,
probably
close
to
the
right
numbers.
A
D
D
A
D
Cool,
so
this
app
is
available.
It's
online.
It's
praise,
distributions.heroku
app.
I
think
it's.
It
should
be
yeah
praise
analysis,
it's
the
top
link
there,
I'm
also
just
running
it
locally
right
now
I
just
cloned
the
repo
and
ran
it
locally
and
for
anyone
who's
interested
in
doing
that,
it's
super
easy.
You
just
install
the
requirements
so,
okay,
here
I
am
in
the
repository.
D
You
go
into
the
ubi
app
and
the
panel
to
run.
It
is
panel,
serve
dot,
pi,
it's
on
the
readme
and
I
think
we
have
to
add
a
requirements
file.
But
so,
if
you
want
to
run
this
locally,
it's
very
responsive,
it
runs
very
fast.
It's
a
little
bit
slower
on
the
deployed
version,
but
it
works
fine
anyways.
So
we
have
the
deployed
version
here
and
my
local
version.
D
So
here
I've
put
three
interventions
together
in
a
dashboard,
so
let's
we
can
toggle
these
off,
and
here
we
have
the
default
praise
impact
hours,
distribution,
so
the
x
axis
is
the
rankings
of
people
it's
sort
of
the
ordering
so
number
zero
index.
Zero
is
the
person
with
the
most
impact
hours
and
then
it
goes
on
this
way.
There's
about
385
this.
This
isn't
the
very
most
latest
data
set,
so
there
would
actually
be
quite
a
few
more
impact
hours
and
more
people
in
the
latest
data
set.
D
We
didn't
quite
get
a
chance
to
sub
out,
but
this
will
give
you
an
idea
what's
available
and
we'll
sub
in
the
latest
data
set,
like
probably
just
after
this
call
on
the
deployed
dashboard.
So
you
can
go
ahead
and
play
around
with
it
yourself
over
on
the
right
here
we
have
the
let's
see.
Did
I
modify
this?
Oh,
I
didn't
okay,
so
these
are
just
the
top
10
impact
hours,
so
number
one,
there's
603
and
without
any
interventions
the
top
impact
hour
holder,
holds
about
6
6.5
of
the
total
distribution.
D
Now
the
genie
coefficient
is
a
measure
of
equality,
that's
generally
applied
to
sort
of
nation
state
economies
in
terms
of
measuring
the
distribution
of
wealth
and
the
lower
the
genie
score
is
the
more
you
have
an
equal
society
where
wealth
is
is
widely
distributed
and
the
higher
and
it
goes
between
zero
and
one.
So
as
it
approaches
one,
you
would
have
an
extremely
high
concentration
of
wealth
in
a
small
number
of
people.
D
A
genie
score
below
0.4
would
be
considered
a
sort
of
a
highly
equal
opportunity,
government
and
or
not
government,
but
economy.
Octopus
is
going
going
to
go
into
this
quite
a
bit
deeper
and
talk
about
different
metrics
and
how
we
should
be
comparing
apples
to
apples
and
because
comparing
the
distribution
of
a
crypto
token
to
the
distribution
of
wealth
in
a
nation
doesn't
really
make
that
much
sense.
D
So
we
have
some
better
metrics
to
look
at,
but
this
is
a
good
starting
point
and
we
can
see
how
this
changes,
as
we
apply
different
kind
of
interventions
here
here,
we're
looking
at
ubi
hours
for
anyone
who
doesn't
know
ubi
stands
for
universal
basic
income.
So
this
is
the
idea
of
let's
just
give
a
give
a
constant
amount
of
hours
to
everyone.
Who's
participated
in
the
tec,
so
everyone
who's
registered
anyone
who's
been
dished.
Praise
ever
should
get
a
base
level
of
tokens
and
that
will
smooth
out
the
distribution
a
little
bit.
D
So
let's
take
a
look
at
that
here
we
can
apply
the
constant
ubi
intervention,
and
so
this
is
set
to
five
hours.
So,
let's
see
okay,
so
you
can
see
how
this
just
ignore
this
bottom
distribution.
For
now
you
can
see
the
entire
distribution
goes
slightly
up
and
down
as
we
toggle
this
on
and
off
you
can
see.
D
D
Out
21
impact
hours
to
everyone
and
say:
hey,
look
we're
really.
You
know
equal
opportunity,
economy
and
yeah,
so
you
can
explore
this.
We
could
give
out
100
ubi
hours
to
everyone.
We
could
give
out
one
hour
and
I
I
think
you
know
I'll
give
a
little
bit
of
my
subjective
experience.
Working
on
this
dashboard,
I
feel
like
anywhere
from
zero
to
25
hours,
could
be
reasonable
for
for
people
to
make
proposals
of
solutions.
That's
just
my
my
intuition.
D
I
do
feel
like
it's
reasonable
to
use
this
intervention,
but
I
I've
also
heard
a
lot
of
really
great
positions
from
community
members
who
say
this
is
this
is
not
what
we
want
or
if
we
do
want
it,
it
should
be
a
very
low
number
and
it's
definitely
worth
hearing
out
those
opinions,
because
they
have
a
lot
of
good
points.
So
we
can
turn
that
off
and
we
can
say:
okay,
maybe
we
don't
want
to
just
airdrop
everyone.
D
Free
tokens
is
what
some
people
would
say,
and
so
maybe
we
want
more
like
a
of
a
targeted
ubi
and
something
a
little
more
sophisticated
than
just
a
completely
equal
distribution
to
everyone.
So
I
came
up
with
this
idea.
Actually
me
and
livy
were
brainstorming
and
we
came
up
with
this
idea
of
a
sort
of
normal
distribution,
like
a
bell
curve
shape
to
reward
like
the
middle
class
hatcher.
D
So
what
I
did
is
I
took
the
average
number
of
impact
hours.
Actually
what
I
did.
I
dropped
off
this
long
tail.
Basically,
all
fifty
percent
of
hatchers
have
three
hours
or
less
so
I
actually
dropped
those
off
out
of
the
calculation
and
then
for
the
top
50
I
took
the
geometric
mean,
let's
just
call
it
the
average
number
of
impact
hours
which
is
43.
So
it's
right
around
here
and
I
then
I
created
this
normal
distribution.
This
is
called
the
gaussian
function.
D
So
we're
not
going
to
give
extra
hours
to
the
people
who
already
have
the
most
hours
and
we're
not
going
to
give
extra
hours
to
people
who
have
four
or
five
hours,
but
everyone
else
in
this
middle
class
people
who
have
around
25
to
50
to
60
70
100
hours,
we're
going
to
give
them
a
bonus
to
sort
of
yeah
inc.
So
so
we'll
see
what
that
looks
like
we
can
apply
the
gaussian,
ubi
and
yeah
so
that
changes
the
genie
coefficient.
D
I
have
it
set
to
15..
We
can
oh,
I
also
have
this,
which
is
the
spread,
so
we
can
target
it
more
around
that
center
or
we
could
flatten
it
out
and
we
can
increase
it
like
so
and
we
could
so
you
can.
It
can
really
become
visible
if
you
make
it
quite
sharp
and
make
it
quite
high,
but
there's
one
property
that
I
think
we
should
maintain
is
that
we
shouldn't
change
the
ordering
of
impact
hours.
D
So
I
don't
think
we
should
ever
have
like
this
decreasing
slope
as
we
move
to
the
left,
because
that's
actually
changing
the
ordering
of
of
people.
So
if
we
keep
this
low
enough
and
we
kind
of
spread
it
out
enough,
then
we
get
this
property
of
that
it
does
not
change
the
ordering
so
yeah.
So
we
can
see-
and
this
is
available-
you
can
play
around
with
this
and
see
what
numbers
are
are
right.
D
I
think
something
around
0.02
and
20
hours
like
looks
pretty
reasonable,
and
you
can
see
the
clear
difference
that
it
makes
it
really
buffers
this
center
area
here
of
ours.
And
then
maybe
we
could
do
a
combination.
So
maybe
we
could
give
everyone
an
extra
three
hours
and
we
could
give
a
20
extra
20
hours
at
the
very
center
of
the
average
and
we
get
our
genie
coefficient
down
to
0.46
and
we've
also
got
a
calculator
here
that
says
the
total
number
of
our
extra
hours
that
we're
distributing.
D
D
So
if
we
reduce
the
deduction
from
85
percent
to
50
percent,
let's
see-
and
we
have
some
metrics
here
so
with
the
current
deductions,
we
have
6044
hours
which
were
deducted,
and
I
just
this
could
be
a
bit
more
sophisticated.
I
just
made
a
simple
ballpark,
I
said
an
hour
is
worth
50
wrapped
x
time.
Maybe
that's
a
bit
high,
but
if
we
just
run
with
that,
then
we
times
this
by
50,
so
we
say:
total
wages
deducted
are
about
300
and
2
000.
D
D
I
guess
this
makes
sense
right.
The
stewards
and
the
paid
contributors
are
kind
of
at
the
center
of
they're
quite
high
on
the
distribution
anyways.
So,
by
having
these
deductions
on
impact
hours
distributed
where
we
are
actually
creating
a
more
equal
distribution,
but,
like
I
said
this
gini
coefficient,
you
know
don't
get
too
attached
to
it.
It's
just
a
number
on
a
screen.
D
It's
take
it
with
a
grain
of
salt.
I
think
it's
nice
to
have
this
number
this
metric.
That
ranges
from
zero
to
one,
but
we'll
hear
from
octopus
some
some
insights
on
alternative
metrics,
so
yeah.
I
hope
this
is
enough
to
give
people
the
confidence
to
go
and
play
around
with
this
tool
and
think
about
how
we
have
these
three
sort
of
independent
distribution
interventions
that
can
be
applied
individually
or
they
can
be
applied
together
and
yeah,
and
that's
that
for
the
this
sort
of
intervention
dashboard
on
the
distributions.
A
No,
I
would
like
oh
octopus
just
jumped
in.
I
think
this
is
so
wonderful,
the
dashboard,
and
you
will
help
a
lot
with
making
the
perfect
proposal
or
playing
around
and
visualizing
that
I
think
there
was
also
some
of
the
categories
discoveries
that
could
be
interesting
to
share
octopus,
if
you
would,
if
you
like,.
H
I
E
E
Okay,
so
I've
I
tried
to
dive.
One
question
that
kept
coming
up
repeatedly
was
about
the
value
of
retweeting
and
the
value
of
attending
meetings.
So
I
tried
to
dive
deeply
into
those
questions.
I
only
looked
at
data
from
period
7
to
period
17,
because
that
was
when
the
discord
server
existed
for
the
tec
and
when
this
the
same
quantifier
system
was
used
through
all
of
those
periods.
E
The
impact
hours
for
retweeting,
so
this
is
not
actually
impact
hour
per
retweet.
This
is
impact
hour
for
a
praise
that
mentions
retweeting,
which
could
potentially
be
multiple
tweets,
but
all
told
the
average
impact
hour
was
0.54
impact
hours
for
such
a
praise
and
they
constituted
about
4
of
all
the
impact
hours
that
were
awarded
during
this
time,
and
I
did
clean
this.
So
this
number
is
accurate
because
some
of
the
retweetings
were
bumped
higher
because
the
quantifiers
were
actually
giving
values
for
something
else.
E
E
And
the
the
varia
there
was
a
lot
of
variability
in
terms
of
how
much
value
retweeting
praises
got.
So
you
can
see
in
eight
there
was
nothing
but
like
in
in
period
seven.
There
was
between
point
two
and
point
three
impact
hours
about
point,
two
five
and
then
in
in
period
14
they
were
highly
valued
at
over
0.8
impact
hours.
So
there
was
a
lot
of
variability
there
and
I
thought
maybe
they
were
like
a
constant
percentage
of
the
impact
hours
per
period,
but
not
varied.
Quite
a
bit.
E
E
E
I
need
you
to
hold
on
one
moment:
okay,
so
there's
these
two
lists
and
if
you
hit
one
word
at
least
one
word
from
each
list,
I
counted
it
as
a
meeting.
So
this
this
caught,
basically
the
things
that
it
should
have.
It
wouldn't
catch
something
like
showing
up
for
today's
research
working
group,
but
it
does
not
catch
hosting
a
party.
E
It
was
like
praise
for
doing
x
and
y
and
attending
a
meeting
and
x
and
y
were
really
big
deals,
so
that
made
some
of
these
praises
be
really
high
and
I
did
not.
I
was
not
able
to
accurately
separate
those,
but
I
just
saw
that
there
weren't
that
many
of
them,
but
that
did
drag
the
average
a
little
bit
higher.
The
average
number
of
impact
hours
for
the
meeting
praises
was
1.14
impact
hours
and
then
median,
which
might
be
more
accurate
because
of
the
high
outliers
is
1.0.
E
So
I
estimate,
based
on
this,
that
if
you
attended
one
meeting
per
week
during
this
january
to
may
period,
you
could
earn
somewhere
between
12
and
20
impact
hours.
For
those
praises,
there
was
again
a
lot
of
variation
of
average
impact,
our
value
based
on
the
period.
Some
of
this
might
be
due
to
the
the
more
important
phrases
that
we
talked
about,
or
you
were
actually
doing
multiple
things.
E
E
So
one
thing
I
thought
was
interesting:
that's
probably
worth
pointing
out,
because
the
the
typical
impact
hour
awarded
varied
so
much
there
were.
Actually,
there
was
actually
this
period
where
the
the
retweets
got
a
very
high
impact
hour
value
period,
14
and
that
that
was
worth
more
than
meetings
in
some
other
periods,
so
of
the
of
the
ones
that
I
looked
at
about.
E
There
were
about
400
meeting
related
praises
that
did
not
get
as
many
impact
hours
as
the
retweet
raised
the
highest
retweet
phrase
and
that's
about
40
percent
hold
on.
I
need
to
keep
my
phone
plugged
in
addie
that's
about
40
of
the
no
yeah,
so
there
were
about
40
percent
of
meetings
that
did
not
get
as
many
impact
hours
as
the
the
highest
retweets,
which
I
thought
was
interesting,
because
people
were
were
pretty
clear
that
they
thought
meetings
was
worth
more
than
retweets.
D
Yeah,
that's
a
good
idea,
we'll
we'll
have
to
have
a
session
where
we
just
cross
reference
results
and
make
sure
we're
using
the
same.
There
have
definitely
been
a
few
different
data
sets
used
and
and
yeah.
So
maybe
we
can
make
a
standard
like
final
if
we
can
get
the
latest
data
and
then
just
say
okay,
this
is
this
is
what
we're
using
for
the
and
now
like
the
we
can
run
that
data
set
through
all
all
of
our
analysis,
results
and
get
kind
of.
Like
final
result,.
A
G
H
Yeah,
I
just
want
to
add.
First,
I
think
it's
I
I
really
want
to
also
emphasize
on
how
awesome
it
is
that
praise
worked
this
well
right,
that
we
have
such
a
great
distribution,
and
this
is
not
based
yeah.
Let's
have
an
applause,
because
I
think
it's
really.
This
is
so
amazing
that
you
have
yeah
it's
a
great.
H
It's
a
great
mechanism,
obviously-
and
I
think
what's
also
great-
is
that
it's,
I
think
we
have
some
kind
of
standard
way
where
you
can
count
contributions
like
retweets,
but
then
we
have
very
subjective
recognition
and
praising-
and-
and
I
mean
that's-
then
you
I
think
when
beginning
praise
it
nev,
we
couldn't
be
sure
if
this
will
work
out
well
because
of
group
dynamics
and
objective
preferences
and
bias
towards
tech
or
bias
towards
social
interaction.
So
you
never
know,
and
to
have
such
a
distribution
is
just
awesome.
H
What
my
question
with
the
with
the
average
impact
hours,
is
rather
what
I
don't
have
a
clear
picture
at
the
moment
is
first,
this
comparison
is
really
valuable
to
see
okay,
how
to
retweet
in
impact
hour
or
result
in
impact
hours
and
compared
to
that
attending
a
meeting.
This
is
very
well
measurable,
both
activities-
and,
I
think
every
so.
My
my
feeling
about
this
is
yes
here.
Retweets
are
overvalued
compared
to
taking
part
in
meetings,
but
yeah.
This
is
should
be
a
matter
of
discussion
as
well.
H
Tech
infrastructure
or
comms,
and
so
I
think
it's
perhaps
not
enough
to
look
at
the
total
amount
for
comparison
and
then
to
see
if
it's
over
or
undervalued.
But
overall,
I
think
this
having
this
comparison
is
super
valuable
to
get
a
picture
on
what
what
was
praised
and
how
we
valued
it.
And
how
does
this
result
in
then
the
hatch
and
decision
making
power?
That's.
H
D
Yeah,
I
think
it
would
be
a
lot
of
the
results
can
be
combined.
I
mean
it
would
be
interesting
to
have
like
double
the
I
feel
like
this
is
like
a
phase.
One
of
the
research
would
be
awesome
to
have
a
phase
two
yeah
and
because
we
could
see
in
relation
like
okay,
we
have
like
the
dashboard.
I
was
showing.
We
have
the
descriptions,
but
could
we
map
those
distributions
to
these
like
it?
D
Could
we
color
the
distribution
chart
by
category
and
see
where,
where
where
that
falls
like
for
for
kind
of
combining
people
with
categories?
So
if
we
could
say
of
the
people
who
have
been
involved
in
various
categories,
where
do
they
sit
along
that
curve
of
the
distribution
and
and
then
looking
at
time
too?
I
think
angela
you
mentioned
like
how
have
this
is
just
a
snapshot
right,
but
how
have
a
lot
of
these?
D
Maybe
there
will
be
a
little
bit
of
technical
investment
on
understanding
how
to
do
things
exactly,
but
I
think
we
could
like
we
could
do
a
retrospective
ubi,
for
example,
it's
possible,
given
the
parameters
of
like
the
dandelion
dow.
I
have
my
intuition
says.
Probably
we
won't
do
that.
I
think
maybe
we'll
do
some
interventions
beforehand,
we'll
get
to
augment
the
impact
hour.
B
H
B
H
I
wouldn't
want
to,
let's
say,
make
this
a
blocker
to
the
hatch,
not
at
all.
It's
rather
better
understand
what
happened
and
maybe
see
the
sensitivities
in
this
in
this
phrase
phase
so
that
we
are
aware
of
there
might
be
a
bias
towards
tweets,
or
just
in
case
we
don't
any.
We
don't
do
any
intervention.
H
A
So
we
are
choosing
to
do
something
very
similar
to
what
we
did
with
the
mission,
vision
and
values
voting
session
and
also
the
params
voting
session
to
choose
the
hatch
configuration
mainly
because
most
of
of
you
that
are
here
are
familiar
with
this
process
already
and
using
token
log.
We
are
allowed
to
have
a
whole
perspective
of
the
stakeholders
and
quadratic
voting
can
help
us
mitigating
some
of
the
issues
we
were
thinking
of.
Some
people
have
like.
A
A
A
The
reason
why
we
chose
to
do
this.
Yes,
so
yes
or
no
for
the
first
four
questions
is
to
help
the
voter,
like
whenever
you're
coming
here
and
you're.
Reading
these
questions,
and
just
yes
or
no,
you
can
have
a
sense
of
what
is
coming
in
the
proposal.
So
maybe,
if
you
don't
agree
with
number
one
or
two,
then
you
don't
even
need
to
read
the
full
thing,
because
we
know
it's
a
time
consuming
process.
So
we
want
to
have
like
the
most
agile
system
possible,
so
number
one.
A
Does
this
proposal
address
that
some
categories
may
be
under
rewarded
and
others
over
rewarded?
That
is
the
case.
We
were
just
talking
about
the
and
the
tweets
and
the
meetings,
for
example,
number
two:
does
this
proposal
address
that
paid
contributors
have
had
a
50
to
85
re
reduction
to
their
total
number
of
impact
hours?
So
would
you
like
to
address
something
like
this
in
your
proposal?
A
Number
three:
does
this
proposal
address
the
foundational
members
of
the
token
engineering
community
may
lack
recognition
for
their
less
visible
work,
so
also
something
very
important
that
started
this
whole
discussion
is
token.
Engineers
have
been
doing
work
for
years
and
is
this
work
have
been
recognized
by
the
prairie
system,
and
is
your
proposal
going
to
tackle
this
issue
and
then
number
four?
A
Does
this
proposal
address
the
distribution
of
impact
powers
in
relation
to
equality
metrics
such
as
gini
coefficient
like
sean
explained
in
the
beginning,
so
those
are
the
problem
sets
that
we
are
proposing
having
solutions
for
so
if,
depending
on
the
questions
you
answered,
yes,
you
would
propose
the
interventions
for
them
and
what
is
the
reasoning
behind
it?
If
someone
wants
to
propose
having
no
interventions
at
all
and
mark
no
and
all
of
them,
you
can
also
propose
that
and
just
share
your
reasoning
for
doing
that.
A
So
I
just
wanted
to
quickly
show
griff's
proposal
griff.
I
apologize
that
he
wasn't
able
to
be
in
this
meeting
and
if
someone
wants
to
see
an
example
of
how
this
was
done,
you
can
go
over
his
proposal
that
it's
very
detailed
for
the
for
the
solutions
he's
suggesting
and
the
the
proposing
and
voting
session
is
open.
A
So
anyone
can
come
and
create
a
new
issue
and
we
are
willing
to
finish
this
process
on
the
next
tuesday
at
this
time
during
the
softcup
meeting
and
we'll
go
over
it
to
prepare
for
the
runoff
so
like
we
had
in
the
other
sessions.
Unless,
where
is
the
forum
post
here?
Unless
a
proposal
has
more
votes
than
all
the
other
proposals
combined,
then
it
is
the
clear
winner.
A
Otherwise
we'll
have
a
session
to
prepare
the
top
three
to
four
submissions
for
a
runoff
vote
and
this
runoff
will
last
until
the
following
thursday.
So
we
are
willing
to
finish
this
voting
process
on
july
1st,
of
course,
if
we
need
more
time,
if
we
see
that
it
wasn't
enough
that
we
didn't
have
proposals
or
votes
enough,
we
can
extend,
but
we're
really
trying
to
think
about
the
timing
and
the
momentum
for
the
hatch
and
and
have
this
moving.
C
A
Yeah,
so
we
would
expect
to
have
most
of
the
proposals
coming
like
right
after
this
meeting
or
in
the
next
couple
of
days.
Since
we
have
this
information
fresh-
and
we
are
seeing
all
of
this
today
and
hopefully
we
can-
we
can
propose
quicker
rather
than
later,
and
it's
always
a
good
practice
to
vote
towards
the
end
of
the
voting
session
on
token
log,
because
what
if
a
new
proposal
comes,
there
is
no
way
to
retract
a
vote.
A
So
hopefully
we
would
have
the
voting
happening,
let's
say
from
thursday
to
tuesday,
but
votings
can
happen
at
any
time.
So,
in
an
ideal,
perfect
scenario,
proposals
would
come
all
of
them
until
thursday,
but
if
people
want
to
submit
later,
it's
also
fine
until
tuesday
and
then
most
of
the
heavy
voting
happens
during
from
thursday
to
tuesday.
K
C
A
Yeah,
so
we
yeah.
That
would
be
great
if
all
proposals
are
there
until
thursday
and
we
can
have
a
collective
effort
to
make
that
happen
and
have
all
the
voting
we'll
stay
and
if
we
feel
like
like,
we
absolutely
need
to
delay
this
process,
then
then
we
can-
and
I
want
to
pass
around
so
we'll
have
one
minute
and
a
half
for
for
who
wants
to
share
so
share
what
you're
thinking
in
general.
A
K
I
don't
know
what
the
right
term
was
matrixes
or
mechanisms
for
measuring
the
data
that
is
different
from
the
gini
coefficient,
because
I
find
the
genie
coefficient
to
be
completely
irrelevant,
like
utterly
irrelevant
to
this
data
set.
So
I
was
wondering
what
those
other
possibilities
might
be.
Am
I
wrong?
Was
that
not
jeff.
D
E
K
G
K
So
I'll
just
say,
my
reflection
really
quickly
is.
I
think
yeah
it'd
be
great
to
look
at
that
video
and
those
different
mechanisms,
because
something
about
the
using
that
kind
of
measurement
for
well
yeah.
Precisely
and
I'm
not
I'm
not
familiar
with
any
of
those,
but
just
my
immediate
reaction
is
it's
going
to
give
a
pretty
skewed
perspective
on
a
community
where
you
do
have
compensated
and
not
compensated
more
members
who
in
ygg
you
did
address
that.
K
Briefly,
saying
that,
of
course,
once
you
had
those
reduced
impact
hours
for
compensated
individuals,
it's
going
to
change
precisely
because
you're
getting
you've
got
you're
getting
it.
Now,
these
these
increased
numbers
for
people
who
are
participating
the
most
obviously,
but
that
is
not
indicative
of
the
of
the
of
the
economy
of
the
entire
community.
I
don't
know
if
that
makes
sense,
I'm
going
to
try
and
articulate
myself
better
in
the
agenda.
J
I
also
want
to
share
something,
and
instead
I
think
that
praise
is
a
very
adaptative
system
and
that
I
loved
the
idea
on
grief's
proposal
where
he
said
that
we
could
have
like
a
t
e
rockstar
praise
session.
I
think
that
that
that
can
also
be
really
good
that,
instead
of
changing
the
data,
adding
some
for
for
the
te
rockstars
and
making
this
a
special
place
session
for
them
for
for
the
speaking
for
the
topic
of
of
the
te
rockstars
that
are
not
so
many
so
much.
B
Have
you
accounted
for
that
like
do
you
know
that
those
t-rock
stars
before
you
do
the
effort,
maybe
yeah
just
check
or
don't
burn
the
impact
hours
and
do
something
else
useful
for
the
community
with
those
by
putting
an
equal
amount
into
some
proposal
bin
or
something
like
that.
So
just
a
comment
or
question.
If,
if
that
is
already.
A
It
is
too
late
to
open
to
open
exceptions
to
a
process
that
has
been
very
like
there's
a
lot
of
people
working
in
that
process
and
making
it
welcoming
for
everyone
who
want
to
participate
so
offering
scholarships
and
helping
in
the
step
by
step,
but
also
it
wouldn't
be
fair
to
the
people
that
have
joined
for
a
legal
shield
to
have
someone
that
is
in
the
in
the
hatch.
That
is
the
fundraising
period.
A
B
B
Because
I
mean
for
for
me,
it
is
very
clear:
you
know
what
what
was
the
waiting
etc,
because
we
were
focused
on
hatching
and
getting
the
token
entering
commons
or
the
common
stack
infrastructure
off
the
ground.
It
was
very
clear
that
the
whole
efforts
to
build
the
the
community
culture
etc
around.
It
are
waited
for
this
for
this
phase
right
and
it
makes
makes
total
sense.
B
Activities
etc
was
more
important
to
build
a
community
of
hatcheries
etc
or
get
attention
than,
for
example,
participating
in
working
groups
in
the
beginning,
etc.
So
saying
it
doesn't
look
that
off
for
me
knowing
what
was
near-term
focus
of
tech
and
hatching
yeah
and
before
you
go
and
do
extra
work,
maybe
really
clarify
whether
that
will
have
the
impact.
L
Cool
yeah
I've
got
a
run
in
in
a
moment
here,
so
we'd
love
to
have
a
chance
to
speak
for
a
little
bit,
so
the
I
think
the
prairie
system,
when
we
first
started
you
know,
was
a
great
way
to
recognize
contributions
across
the
board.
I
think
you
know
looking
back,
I
don't
think
there's
anyone
in
this
community
who
worked,
you
know
20
times
harder
than
anyone
else,
at
least
among
the
the
engaged
participants
you
know.
L
So
it's
I
find
the
distribution
a
little
bit
tricky
because
I
understand
there
are
people
who
took
pay
and
people
who
didn't.
I
think
the
85
percent
was
probably
a
little
extreme.
Looking
back,
of
course,
at
the
time
we
were
just
picking
a
number,
we
thought:
hey,
there's
a
number
and
we
can
adjust
it
in
the
future.
We
never
adjust
it
in
the
future.
This
is
potentially
an
opportunity
to
adjust
that
moving
forward.
You
know
both
in
the
future
or
pre-hatch,
as
the
community
decides.
L
I
do
kind
of
think
there
are
some
like
kind
of
like
game
ways
to
game
this
like.
If
I
look
back,
I
would
say:
okay,
you
know
from
octopus's
analysis
joining
a
call
per
week
for
four
months
and
doing
a
couple
of
retweets
would
get
me
the
majority
of
my
impact
hours
over
doing
all
of
the
things
that
I
did.
I
find
the
praise
system
a
little
bit
tricky
because
you
have
to
do
it's
not
just
the
work.
L
L
This
is,
I
think,
the
bulk
of
the
work
that
kind
of
got
missed
by
in
that
praise
kind
of
perception,
and
that's
one
of
the
things
that
I
really
want
to
make
sure
that
tes
are
at
least
as
well
represented
as
we
can
get
them
in
this
list,
because
I
think
tes
are
are
critical
to
the
tec
moving
forward
and
it's
it's
sort
of
this.
You
know
recognition
breeding,
goodwill,
breeding,
more
projects
breeding.
You
know
we,
we
grow
the
pie
together,
we
can,
we
can
subdivide
the
pie
and
say
hey.
L
L
L
C
I
gotta
jump
too
for
a
research
call.
Sadly,
I
didn't
even
realize
that
there
was
a
conflict
okay,
so
I
just
share
a
little
bit
of
experience
in
saying
I
mean
I
number
one
want
to
express
gratitude
for
all
the
work.
That's
been
done.
Just
sean
octopus,
muhammad,
you
guys,
are
just
blowing
the
whole
socks
off.
I
don't
know
I
don't
have
the
right
analogy,
but
this
is
amazing,
especially
for
the
future
of
token
engineering.
So
the
work
here
is
incredibly
valuable
and
I
don't
know
I
realized
yesterday.
C
I
don't
know
any
other
community
that
could
handle
this
with
such
grace.
So
I've
been
really
impressed
with
how
we've
been
able
to
turn
this
into
something
productive,
but
I'll
just
share
a
little
bit
of
my
experience.
I
guess
that
I've
been
having
realizations
throughout
this
process.
I
also
have
been
on
all
sides.
I've
done
the
praise
quanting,
I
you
know
started
with
livia
griff
in
this
community
last
july
or
august
and
watched
this
whole
thing
unfold,
and
I
had
questions
throughout
that.
C
I
didn't
really
raise
and
then
I
started
to
realize
quickly
when
we
looked
into
things
and
even
myself
like
I
was
a
core
contributor
I
was
inside,
I
was
pushing
from
all
directions
and
I
was
very
visible.
So
I
was
getting
praised
loads
and
I
was
very
high
on
the
list
and
now
because
I've
moved
a
lot
of
my
work
into
token
engineering.
Research
suddenly-
and
I
don't
mind
for
my
personal
sake,
I'm
just
using
myself
an
example
as
an
example.
C
Suddenly,
I'm
not
you
know
as
visible,
so
I've
seen
this
shift
that
jeff
is
kind
of
talking
about,
and
I
think
for
me
too,
when
we
originally
started
back
in
august
of
last
year,
we
had
started
with
this
intention
that
we
were
going
to
we
you
know
needed
to
push.
I
guess
some
of
the
contention
early
on
was
rewarding
higher
for
t
building
the
tec
versus
te
work,
and
we
said
okay,
we're
going
to
start
now,
because
we
have
to
start
this
commons.
C
This
dow
we
have
to
reward
higher,
but
at
some
point
we'll
shift-
and
I
feel
like
that
point
never
really
came
or
this
is
the
point
now
to
then
okay,
the
the
house
has
been
built
and
then
rewarding
as
well
some
others.
So
I
just
feel
like
now's
the
opportunity
to
to
make
that
shift,
and
the
last
thing
I'll
say
is
just
that
for
me.
Looking
at
the
distribution
of
the
buckets,
I
feel
wouldn't
be,
you
know
the
ideal
for
me.
C
So
I
don't
know
if
there
are
some
other
considerations
for
normalizing
or
applying
average
for
standard
ih
awards,
like
even
you
know,
sean
and
octopus
were
presenting
even
the
same
actions
were
had
a
lot
of
variation,
so
maybe
there's
some
adjustments.
We
can
apply
there
as
well
and
based
on
categories
and
then
finally,
sean
had
mentioned
that
we
were
not
affecting
the
order
or
ranking,
and
I
know
this
is
probably
the
most
contentious
part,
but
I
don't
think
we
can
say
that
everyone's
in
agreement
with
that,
I'm
not
sure
how
to
address
this.
C
So
I
hope
we
can
look
past
our
own,
you
know
desires
and
that
we're
able
to
think
of
this
as
sharing
rather
than
taking
from
anyone-
and
I
would
happily
give
away
all
of
my
hours
and
brought
this
up
the
other
day.
I
wish
I
could
gift
some
hours
to
people
who
I
feel
have
been
undervalued.
So
I
hope
we
can
all
keep
this
in
mind
as
we
go
through
this
process
and
I'll
pass
on
to
whoever
wants
to
speak
next.
D
Yeah
I'll
go
next
because
I
think
I
have
some
points
that
are
related
and
awesome.
I
really
appreciate
both
jeff
and
jessica
with
all
those
really
good
points.
I
think
the
gifting
praise
is
awesome
like
I
think
that
should
be
a
proposal.
I
don't
know
how
it
would
be
implemented
exactly,
but
maybe
it's
doable
and
maybe
think
it
through.
I
was
gonna,
say
I
you
know.
D
Oh
yeah,
that
thing
that
that
person
did
was
so
grateful
like
so
impactful
to
the
community,
and
it's
probably
undervalued,
but
the
beautiful
thing
about
this
is
we?
Can
we
don't
need
to
augment
the
system?
We
can
actually
use
them
as
it
is
to
fix
this.
We
can
jump
in
and
we
can
just
dish.
We
can
dish,
dish,
dish
and
dish
praise
before
the
hatch,
and
so
that's
that's
one
pretty
cool
proposal
where
we
don't
have
to
there's
no
technical
solution.
D
D
So
I
really
like
the
idea
of
infinite
investing
tokens
like
tokens
that
you
can't
trade,
so
they
essentially
have
no
monetary
value,
but
they
represent
governance
in
the
system.
So
I
I
I'll
put
forward
or
I'll
look
forward
to
seeing
some
sort
of
proposal
that
maybe
a
combination,
so
maybe
85
deductions
was
too
much
for
the
paid
workers,
so
maybe
sliding
that
down.
D
Deductions
is
probably
something
that's
quite
reasonable,
maybe
six
percent-
I
don't
know
and
then
also
a
prospective
future
where
those
tokens
are.
Maybe
a
hundred
percent
is
actually
too
much.
I
don't
know
like
to
have
this
sort
of
purely
governance,
infinitely
vested
token
that
offsets
that,
but
I
think
I
think
the
stewards
having
governance
influence
for
the
work
that
they've
done
and
the
commitments
they've
made
is,
is
a
important
concept.
D
So
I
like
that,
infinite
vesting
tokens.
I
like
this,
the
slider
on
moving
away
from
the
85
percent
extreme.
I
really
like
the
the
gifting
and
rock
star
ideas,
and
I
think
I
I'll
like
to
see
so
I
think
a
little
bit
of
ubi
like
I.
I
definitely
think
like
two
hours
ubi
to
everyone
is
better
than
zero
and
I
don't
know
how
high
we
would
want
to
go
that,
but
I
would
like
to
see
something
like
that
and
gaussian
equals.
D
A
J
Why
can
I
not
be
at
a
te
if
I
am
working
for
the
token
engineering
ecosystem
and
adding
value?
That
is
not
the
the
the
the
typical
te
work
or
it's
not
like
one
of
the
most
developed
pet
petals
of
the
flower,
but
is
coming
from
other
petals
of
the
flower
that
shouldn't
be
considered
less
than
the
work.
That
is
like
hard
te
work.
That
is
like
around
systems
and
framework
and
around
yeah
tools.
G
Hello
everyone.
I
just
wanted
to
comment
on
something
which
is
basically
the
idea
of
that.
Only
I
mean
I
don't
think
that
only
te
people
are
the
only
ones
that
could
be
unrepresented.
There
are
people
who
are
in
the
cultural
build
that
could
be
also
unrepresented.
So
it's,
I
think,
the
scope
of
just
thinking
talking
engineers
are
the
only
ones
represented
here.
It's
a
little
bit,
not
accurate,
and
besides
that,
I
think
the
work.
It's
amazing.
G
D
M
M
M
Yeah,
like
I
had
a
lot
of
things
about
this,
because
I
I
guess
many
people
have
come
about
with
fantastic
ideas
to
to
make
this
system
further
or
to
move
it
towards
a
better
understanding
for
what
the
thick
that
commons
was
trying
to
do.
So
I
think
that
someone
who
who
was
another
one
was
this.
We
could
say
this
meeting
committee,
who
decided
a
little
bit
what
the
prey
system
was
being
built
for.
M
M
I
guess
the
the
the
things
that
angela
mentioned
as
well
is
are
very
useful,
so
you
are
obtaining
what
you
were
trying
to
do
for
never
beginning.
So
this
is
like
mechanistic
as
well
and
like
little
tricks
in
this
middle
class,
stakeholders
would
do
even
if
it's
like
something
general,
you
give
20
to
three
impact
towers
from
the
beginning
to
all
these
middle
stakeholders.
M
Yes,
we
got
so
be
aware
of
that
and
yeah
the
best
thing
in
infinite
western
is
a
good
idea
from
from
my
view
and
coming
up
with
something
intermediate,
I
guess
so
yeah.
Let's.
Let's
hope
there
is
a
proposal
which
is
fair
for
for
everyone,
and
so
sister
said,
which
is
also
very
interesting
like
if
you
are
trying
not
to
burn
the
tokens
from
the
very
beginning
for
the
hatch
for
the
token
engineers
that
would
be.
M
N
N
I
think
it
was
more
around
scene
versus
unseen
work
and
more
about
the
work,
that's
very
visible
to
the
community,
because
we're
participating
it's
highly
participatory
so
that
we're
on
the
calls
and
the
discord
on
top
of
everything
having
one-on-one
sinks
versus
the
work.
That's
invisible
in
some
regards,
except
for
these.
N
You
know
I
already
did
advice
process
with
both
common
stack
and
previous
soft
gov
around
my
thinking,
which
is
the
85
deduction
of
impact
hours
made
sense
in
the
very
beginning
of
this
project,
where
there
was
two
or
three
people
who
started
it
and
they
were
all
compensated
by
common
stack.
So
as
the
community,
so
they
were
very
visible,
very
present
and
it
would
have
been
to
the
detriment
of
the
community.
Had
those
people
had
their
entire
impact
hours
credited
to
them
that
they've
earned.
N
So
it
sort
of
made
sense
in
the
very
beginning,
but
as
time
went
on
and
as
more
community
members
joined
and
also
had
positions
of
high
visibility,
it
started
to
make
less
and
less
sense
and
it
never
was
actually
adjusted
to
the
changing
environment
of
the
people
that
were
compensated,
and
then
I
guess
the
also
thing
I
wanted
to
say
about
the
compensation
I
mean.
I
have
a
separate
proposal.
That's
completely
independent
of
this
about
how
we
should
adjust
praise
going
forward
which
it
and
my
proposal
would
be
just
to
get
rid
of
it.
N
Actually,
it
falls
too
wide
people
who
are
compensated
but
really
work
on
other
projects
entirely
or
not
even
in
the
tec,
are
also
deducted
for
their
participation
in
the
t
when
they
do
participate
in
the
tc.
They
also
have
an
85
reduction,
even
though
they're
not
daily
they're,
not
visible
in
the
tc,
or
they
don't
do
a
lot
of
work
here
and
then
the
last
thing
is,
it
doesn't
really
take
into
people's
into
consideration
people's
unique
circumstances.
I
I
I
I
I
Do
great
interventions
that
breaks
how
things
have
been
doing
in
that
sense,
I
like
the
idea
of
doing
more
praise
to
people
using
the
same
system
or
even
even
giving
impact
hours
that
I
I
probably
would
like
to
give
impact
hours
to
people
who
I
think
that
are
not
represented
enough
example.
I
I
will
give
impactors
from
myself
to
to
paolo
and
to
other
people
that
I
think
that
are
too
low.
I
J
D
D
So
this
is
a
clustering,
so
I'm
pretty
sure
it's.
This
is
the
algorithmic
approach,
so
let's
say
we
have
every
day
of
the
week
and
we
have
the
amount.
The
average
amount
of
impact
hours
per
praise
goes
from
zero
to
one
hours.
It
looks
like,
and
then
we
have
a
grouping.
So
it's
kind
of
hard
to
read
this,
but
you
have
to
spend
some
time
at
with
it
and
squint
and
you
can
start
to
see
different
days
of
the
week
and
just
different
properties.
D
A
D
It
could
be
that
or
it
could
be,
that
the
highest
higher
praise
is
given
on
sunday.
So
it's
it's
hard
to
buy
into
this
too
much
and
make
conclusions,
but
we
can
see
some
interesting
things
like
there's
a
bimodal
distribution
for
friday,
which
shows
that
there
is
this
very
large
cluster
and
then
there's
a
smaller
higher
cluster
in
the
0.6
and
0.7
range,
and
so
this
is
just
kind
of
a
tool
for
people
to
play
around
with
and
tried
all
the
different
variables.
D
And
when
you
see
the
colors
here,
these
are
automatic
clusterings.
So
everything
in
green,
for
example,
cluster
number
three
at
the
top.
The
the
the
algorithm
that
we
use
found
that
those
phrases
have
similar
properties
and
those
properties
are
a
combination
of
the
day.
They
were
praised
on
the
amount
of
praise
that
was
given
and
then,
let's
see
what
it
says
on
the
left
description
k
mean
take
is
based
on
average
percent
and
impact
hour
per
praise.