-model: it seeks to have every node agree on what the most recent
-version of the variable is. In this way, a node can prompt the network
-to reach consistency on a new value for a variable by telling the
-network it is newer. If several nodes all decide they need to update
-the variable, dissemination ensures that the network converges on a
-single value. Consistency does not mean that every node will see every
-possible value the variable takes: it only means that the network will
-eventually agree on what the newest is. This means that if a node is
-disconnected from a network and the network goes through eight
-versions of a disseminated value, when it rejoins the network it will
-only see the most recent.</p>
+model: it seeks to have every node agree on the most recent version of
+the variable. In this way, a node can prompt the network to reach
+consistency on a new value for a variable by telling the network it is
+newer. If several nodes all decide to update the variable,
+dissemination ensures that the network converges on a single one of
+the updates.</p>
+<p>Consistency does not mean that every node will see every possible
+value the variable takes: it only means that the network will
+eventually agree on what the newest is. If a node is disconnected from
+a network and the network goes through eight updates to a shared
+variable, when it rejoins the network it will only see the most
+recent.</p>