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Comparing the left column to the right column shows that adding an edge to a disconnected pair of edges increased the similarity between their contribution levels.
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Some have even asked for suggestions from party officials for ways to disguise their contribution levels.
You'll never guess where their contribution levels are projected to be!
Under each system, the government, employers and employees would all maintain their existing contribution levels.
Figure 3 summarises all challenges and properties with their specific contribution levels for the evaluated framework.
The relationships between contribution levels in the other blocks and FFFS were also non-significant.
There was no correlation between contribution levels under implemented punishment conditions and FFFS (r = −.001, p =.97).
Further, contrary to our predictions, we did not find a correlation between FFFS and contribution levels under implemented punishment.
Specifically when punishment was implemented there was no significant correlation between BIS-anxiety and contribution levels for either free riders or non-free riders.
On closer inspection, therefore, Cassar's results are probably consistent with ours that, is differences in contribution levels between network structures are not significant.
There were no significant differences in the contribution levels between those who experienced the implemented punishment block before the non-implemented punishment block as compared to those who had experienced these blocks in the reversed order: the implemented punishment block first (t (77) = −1.41, ns), the non-implemented punishment block first (t (77) = −1.28, ns).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com