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    <title>OAR@UM Collection:</title>
    <link>https://www.um.edu.mt/library/oar/handle/123456789/132710</link>
    <description />
    <pubDate>Tue, 28 Apr 2026 04:48:18 GMT</pubDate>
    <dc:date>2026-04-28T04:48:18Z</dc:date>
    <item>
      <title>Cutting edge recruitment best practices : a REA study</title>
      <link>https://www.um.edu.mt/library/oar/handle/123456789/141836</link>
      <description>Title: Cutting edge recruitment best practices : a REA study
Abstract: From a structural functionalistic perspective, this dissertation sought to understand how &#xD;
best to align the processes of formal education, and the processes of recruitment, such that both &#xD;
develop in syntony, rather than in disharmony. Two knowledge synthesis tools were employed. &#xD;
In the first part (Chapters 1 and 2 specifically, together with their related appendices), a &#xD;
traditional literature review was undertaken, for the purpose of understanding how modern &#xD;
economies are trending to begin with, and thus extrapolate the likely economic scenarios of the &#xD;
future. The evidence relied upon in this review consisted of expert opinion, and up-to-date &#xD;
statistical information. In the second part (Chapters 3 and 4 specifically, together with their &#xD;
related appendices), a Rapid Evidence Assessment (REA) of influential academic literature was &#xD;
undertaken. The REA specifically analysed thirty-one sources, specifically consisting of sixteen &#xD;
meta-analyses, two systematic reviews, four cross-sectional studies, and nine traditional &#xD;
literature reviews, that spanned almost half a century of research, from 1973 to 2022 (please note &#xD;
Appendix 2 specifically). The systematic manner (please note Chapter 3) by which these thirty-one sources were identified and selected, was novel, and the results appear to have been&#xD;
promising and fruitful. Additionally, apart from the systematic overview of the said academic &#xD;
literature, this REA made an original discovery concerning the criteria of job performance, with &#xD;
the systematically collected evidence clearly suggesting that there is a hierarchical order to these &#xD;
criteria, meaning that some of these criteria consistently yield higher validities than others, &#xD;
irrespective of the type of predictor or occupational category (please note RQ3’s Executive &#xD;
Summary). The key factual findings of this dissertation have been listed in Appendices 32 and &#xD;
33, for the reader’s convenience.
Description: M.A.(Melit.)</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
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      <dc:date>2025-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>The challenges of deepfake technology on the decision-making processes within law enforcement : a study within the EU landscape</title>
      <link>https://www.um.edu.mt/library/oar/handle/123456789/141835</link>
      <description>Title: The challenges of deepfake technology on the decision-making processes within law enforcement : a study within the EU landscape
Abstract: This study aims to scrutinize the challenges posed by deepfake technology in the &#xD;
decision-making processes of law enforcement, both locally and across Europe, categorizing them &#xD;
into three key areas: &#xD;
 Knowledge and Awareness: Assessing law enforcement officers’ familiarity with deepfake &#xD;
technologies, associated crimes, and the operational challenges encountered. &#xD;
 Evidence Management: Identifying difficulties in detecting deepfake content, preserving its &#xD;
evidential integrity, and ensuring its admissibility. &#xD;
 Legal and Procedural Challenges: Analyzing legislative frameworks and courtroom &#xD;
practices regarding deepfake evidence, and current initiatives to mitigate misuse. &#xD;
 A qualitative research approach was employed, utilizing a structured questionnaire &#xD;
distributed through intermediaries to law enforcement agencies across the EU, supplemented by &#xD;
secondary data and case studies to enhance validity through triangulation. Twelve officers responded &#xD;
(4 from Malta and 8 from other EU countries), all with direct or indirect experience of deepfakes in &#xD;
criminal investigations. &#xD;
 There was a broad consensus among respondents on a significant lack of preparedness &#xD;
in addressing deepfake threats, both in terms of detection capabilities and evidentiary handling. &#xD;
Officers reported substantial difficulties in reliably identifying manipulated media, preserving its &#xD;
chain of custody, and navigating inconsistent legal standards across jurisdictions. Detection &#xD;
challenges are compounded by rapid advances in synthetic media quality, often outpacing available &#xD;
forensic tools. &#xD;
 In contrast to findings from EU respondents, studies from the United States and &#xD;
Australia show a slightly higher level of operational preparedness, often attributed to earlier adoption &#xD;
of digital forensic techniques and a more rapid development of AI-focused legal scholarship. &#xD;
However, even in these jurisdictions, significant concerns remain about evidentiary reliability and &#xD;
procedural fairness when presenting AI-generated content. &#xD;
 Deepfake evidence presents unique admissibility challenges, such as establishing &#xD;
authenticity, reliability, and the absence of tampering. Courts are struggling to develop consistent &#xD;
standards, and current digital evidence frameworks often lack explicit provisions for synthetic media. &#xD;
There is a growing debate over whether new evidentiary rules are needed or if existing frameworks &#xD;
(such as chain of custody, expert testimony, and metadata analysis) can adapt adequately. &#xD;
 On the ground, officers report that gaps in regulation and procedural clarity lead to &#xD;
uncertainties in evidence collection and presentation, delaying investigations or causing reliance on &#xD;
expert witnesses to establish basic authenticity. Prosecutors express concern over juror perceptions &#xD;
of manipulated media and the risk of undermining trust in legitimate evidence. These issues often &#xD;
translate into higher costs, longer case preparation times, and difficulties in achieving convictions.
Description: M.A.(Melit.)</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://www.um.edu.mt/library/oar/handle/123456789/141835</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>From paper to practice : a critical examination of the role local student dissertations have in supporting evidence-based practices in social work</title>
      <link>https://www.um.edu.mt/library/oar/handle/123456789/141767</link>
      <description>Title: From paper to practice : a critical examination of the role local student dissertations have in supporting evidence-based practices in social work
Abstract: This study explored the extent local student dissertations can support evidence-based practices &#xD;
in social work. Dissertations are often an overlooked resource but strategically arranging their &#xD;
position could transform them into contextualised sources of evidence with the potential of&#xD;
narrowing the local research-to-practice gap. Two research questions were formulated to define &#xD;
the scope of the research, one targeting the academic aspect of the dissertations whilst the other &#xD;
targeted their use in practice. A mixed methods approach was employed for this study. First, a &#xD;
quantitative, descriptive analysis paved the way by describing the salient trends and &#xD;
characteristics of all social work dissertations submitted at the University of Malta between &#xD;
2019 and 2023. Second, eight qualitative semi-structured interviews were carried out with four &#xD;
senior academics and four social services managerial employees to answer each research &#xD;
question, respectively. A deductive thematic analysis was employed to structure the findings &#xD;
obtained from the interviews into six overarching themes. The quantitative findings &#xD;
demonstrated that social work dissertations were condensed at undergraduate level, adopted a &#xD;
qualitative strategy and an observational, descriptive design. Social workers were the most &#xD;
targeted population and governmental intermediary institutions were the most prevalent. Most &#xD;
samples were gathered from Malta and the top four most researched topics were ‘social work &#xD;
practice’, ‘violence against women’, ‘disability’, and ‘substance misuse and addictive &#xD;
behaviours’. The qualitative findings indicated that both academics and managerial employees&#xD;
lack a thorough conceptualisation of evidence-based practices, the research-to-practice gap &#xD;
stems from both human and environmental constraints and published studies are extensively &#xD;
favoured over unpublished ones. The academics demonstrated a clear distinction between the &#xD;
expectations imposed across the different academic levels whereas an underdeveloped &#xD;
publication culture within the Department limits the extent dissertations are shared. Managerial &#xD;
employees are not particularly inclined to refer to undergraduate dissertations because of their &#xD;
limited practicality. It was determined that although undergraduates make up the biggest &#xD;
cohorts, the students lack the necessary analytical skills and field experience to produce &#xD;
dissertations with strong practical implications. Consequently, dissertations are not embedded &#xD;
in the practice toolkit of most practitioners and are overlooked as possible sources of &#xD;
contextualised evidence. To improve the quality and practicality of dissertations, the dynamics &#xD;
surrounding university-agency collaborations are discussed. The concept of research waste is &#xD;
explored to address the current misuse of local research resources. The study will conclude &#xD;
with actionable recommendations to enhance the integration of dissertations into practice.
Description: M.A.(Melit.)</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://www.um.edu.mt/library/oar/handle/123456789/141767</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Optimising monetisation through social media platforms : a case study on MaltaDaily</title>
      <link>https://www.um.edu.mt/library/oar/handle/123456789/139952</link>
      <description>Title: Optimising monetisation through social media platforms : a case study on MaltaDaily
Abstract: This study investigates the monetisation strategies employed by social media platforms, using MD as a case study. MD has rapidly become a leading digital media outlet in Malta, adapting traditional media approaches to a social media-first environment. Adopting a qualitative methodology, nine semi-structured interviews were conducted with internal stakeholders, clients, and external experts. Thematic analysis revealed six key themes: authenticity and trust, monetisation models, social media-first content strategy, engagement and performance metrics, challenges in a small, saturated market, and innovation and future growth opportunities. Findings show that MD relies heavily on direct advertising but is actively diversifying its revenue streams through events, subscription models, and service-based income. Authenticity, relatable content, and ethical brand partnerships were identified as critical to sustaining engagement and trust. However, Malta’s limited geographic and demographic size presents distinct challenges, requiring continuous innovation and the adoption of data-driven strategies. The research concludes that diversified monetisation, investment in audience analytics, and technological innovation are essential for MD’s long-term sustainability. Additional to these findings, it provides practical recommendations and contributes to the growing academic discourse on social media entrepreneurship in niche markets, highlighting the unique dynamics of operating within smaller economies.
Description: B.Sc. Bus.&amp; IT(Melit.)</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://www.um.edu.mt/library/oar/handle/123456789/139952</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
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