docs: def Borda_mean_winners(self, profile):
          """
          Returns a list that associates all the winners of a profile under The Borda-mean rule.
  
          :ivar Profile profile: A Profile object that represents an election profile.
          """
          n_candidates = profile.numCands
          prefcounts = profile.getPreferenceCounts()
          len_prefcounts = len(prefcounts)
          rankmaps = profile.getRankMaps()
          values = zeros([len_prefcounts, n_candidates], dtype=int)
          if min(list(rankmaps[0].keys())) == 0:
              delta = 0
          else:
              delta = 1
          for i in range(len_prefcounts):
              for j in range(delta, n_candidates + delta):
                  values[i][j - delta] = rankmaps[i][j]
          # print("values=", values)
          mat0 = self._build_mat(values, n_candidates, prefcounts)
          borda = [0 for i in range(n_candidates)]
          for i in range(n_candidates):
              borda[i] = sum([mat0[i, j] for j in range(n_candidates)])
          borda_mean = mean(borda)
          bin_winners_list = [int(borda[i] >= borda_mean) for i in range(n_candidates)]
          return bin_winners_list