Very little, it could be argued. Trained study staff conducted semi-structured interviews with participants before the pandemic, between April 2018 and August 2019. As such, they will admit only of solutions that are similarly social, economic, and political. WNLU uses deep learning to extract metadata from keywords, categories, sentiment, emotion and syntax. Most of these causes and factors are social, economic, and political in character.
Semi-authenticated interviews are carried out by staff members who actually interviewed participants in the study.
( z0 carry-out :ARG0 ( z1 person :ARG0-of ( z2 have-org-role :ARG1 ( z3 staff ) :ARG2 ( z4 member ) ) :ARG0-of ( z5 interview :ARG1 ( z6 person :ARG0-of ( z7 participate :ARG1 ( z8 study ) ) ) :ARG1-of ( z9 actual ) ) ) :ARG1 ( z10 interview :ARG1-of ( z11 verify :degree ( z12 semi ) ) ) )
(z0 / carry-out-03
    :ARG0 (z1 / person
              :ARG0-of (z2 / have-org-role-91
                           :ARG1 (z3 / staff)
                           :ARG2 (z4 / member))
              :ARG0-of (z5 / interview-01
                           :ARG1 (z6 / person
                                     :ARG0-of (z7 / participate-01
                                                  :ARG1 (z8 / study-01)))
                           :ARG1-of (z9 / actual-02)))
    :ARG1 (z10 / interview-01
               :ARG1-of (z11 / verify-01
                             :degree (z12 / semi))))
Semi - authenticated interviews are carried out by staff members who actually interviewed participants in the study .
z11 :degree z12
z10 :ARG1-of z11
z0 :ARG1 z10
z0 :ARG0 z1
z1 :ARG0-of z2
z2 :ARG1 z3
z2 :ARG2 z4
z5 :ARG1-of z9
z1 :ARG0-of z5
z5 :ARG1 z6
z6 :ARG0-of z7
z7 :ARG1 z8