Baker, Louise Adele
Description
This thesis examines the utility of computational methods as
applied to a qualitative data set arising from full life, oral
history interviews. The overarching question proposed is: ‘What
can computational methods, applied to a qualitative data set
arising from full life oral histories, add to our understanding
of the lives and networks of Australia’s trailblazing women
lawyers?’ The nature of this topic dictates the use of selected
software programs and a...[Show more] comparative analysis of the usefulness of
these software programs for effective data interrogation.
The project was developed experimentally and experientially to
test the hypothesis that through the application of computational
methods to qualitative data, researchers can learn more about
data than would be possible through the more human centric
analytical methods traditionally employed by the humanities and
social sciences.
The project has utilsed a grounded theory approach, applying this
to the data arising from full life oral history interviews with
sixteen of Australia’s trailblazing women lawyers.
Internationally, the use of oral history to uncover the
biographical and cultural history of trailblazing women lawyers
is established. However, in Australia, empirical enquires have
erased biographical details and neglected the storytelling
element of oral history. Women lawyers stand at the professional
forefront of women’s participation in Australian civic life.
The last 100 years has seen many new women pioneers at the
frontier of the Australian legal profession, as they enter
previously male-only areas of practice, adopt new ways of
practicing, take up elite legal positions and enter the
profession from increasingly diverse backgrounds. The majority of
the women included in this study are not mentioned in any public
record, thereby limiting the historical picture of women’s
experiences upon first entering the legal profession. This
project seeks to fill that gap by providing a holistic picture of
the lives of the trailblazer, through their individual and shared
networks.
Iterative strategies are utilised and the project methodology
necessitated working back and forth between the data and
developing analysis, whilst utilising comparative methods. The
hypothesis is that through continually re-engaging with the data,
further research questions arise and can then be explored.
Further questions, crucial to answering the overall question
posed in this thesis, include:
• What can database technology including the relational
database, the Online Heritage Resource Manager (OHRM) and graph
database Neo4j, tell us about the lives of the trailblazers?
• How does qualitative data representation (in this thesis, the
addition of network visualisation through ConneX) add value to
research outcomes?
Each of these questions assists in determining the added value of
the computational approach. This is the key goal of this project
as it seeks to identify what this method of research enables us
to illuminate about this particular group of trailblazing women
lawyers.
The conclusions of this project confirm the assertion that
computation helps to reveal patterns within the lives of this
select group of trailblazing women lawyers. Quantitative data,
including the total number of ‘nodes,’ or ‘entities’ and
relationship counts were explored, as was extensive qualitative
data, including such shared concepts as ‘experience of
discrimination’ and ‘periods living overseas.’ Furthermore,
the query, ‘shortest path,’ as discussed in relation to the
establishment of graph theory, revealed the most frequently
occurring ties shared across the set of trailblazers as a whole.
The three key shared key findings amongst this particular group
included having attended a single-sex school, access to mentors
and participation in a professional association, in this case,
the Women Lawyers Association. To this end, it is recommenced
that socio-legal and socio-scientific researchers seek to
incorporate digital tools to help curate, explore and analyse
qualitative data.
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.