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This study aims to explore the implementation of artificial intelligence (AI) in archival practice by presenting the thoughts and opinions of working archival practitioners. It contributes to the extant literature with a fresh perspective, expanding the discussion on AI adoption by investigating how it influences the perceptions of digital archival expertise.

In this study a two-phase data collection consisting of four online focus groups was held to gather the opinions of international archives and digital preservation professionals (n = 16), that participated on a volunteer basis. The qualitative analysis of the transcripts was performed using template analysis, a style of thematic analysis.

Four main themes were identified: fitting AI into day to day practice; the responsible use of (AI) technology; managing expectations (about AI adoption) and bias associated with the use of AI. The analysis suggests that AI adoption combined with hindsight about digitisation as a disruptive technology might provide archival practitioners with a framework for re-defining, advocating and outlining digital archival expertise.

The volunteer basis of this study meant that the sample was not representative or generalisable.

Although the results of this research are not generalisable, they shed light on the challenges prospected by the implementation of AI in the archives and for the digital curation professionals dealing with this change. The evolution of the characterisation of digital archival expertise is a topic reserved for future research.

This paper reports results of analyses made at an all-female Gulf Arab university measuring the nature and extent of biases in students' evaluation of faculty. Comparisons are made with research reporting the nature of similar relationships in North America. Two issues are investigated: 1) What variables (if any) bias faculty evaluation results at an all-female Arab university? 2) Are biasing variables different in nature or magnitude to those reported at North America universities? Using the population of 13,300 faculty evaluation records collected over two school years at Zayed University, correlations of faculty evaluation results to nine potentially biasing factors are made. Results show biases to faculty evaluation results do exist. However, biases are small, and strikingly similar in nature to those reported at North American universities.

Among the many factors fueling the inflationary tendencies in an economy such as monetary shocks, structural shocks, demand shocks, external shocks and demographic changes, the issue of inflation (INF) has also been found to be related to fiscal policy decisions of the government. The purpose of this study is to investigate the inflationary tendencies in India particularly from the fiscal point of view. The study also examines the influence of other potential determinants such as output growth rate, interest rate, trade-openness (TO) and oil price inflation (OPI).

To examine the dynamic nature of association between fiscal deficit and inflation, the study applies the Toda-Yamamoto (1995) test and Breitung and Candelon (2006) test to investigate the nature of causality in time and frequency domain frameworks. In addition, to scrutinize the possibility of a long-run association, that too from an asymmetric point of view, the study applies a Non-linear Autoregressive Distributed lag model (NARDL) given by Shin et al. (2014). Finally, non-linear cumulative dynamic multipliers are used to trace the traverse between disequilibrium position of short-run and subsequent long-run equilibrium of the system.

The authors found a unidirectional causality from fiscal deficit to inflation in case of time domain analysis and no feedback causality is reported. However, in case of frequency domain design, causality from fiscal deficit to inflation is found at low frequencies only, i.e. no short-run causality is established and hence dynamic nature of the relationship between the two variables is vindicated. Using NARDL model, the results document the existence of an asymmetric long-run direct association between fiscal deficit and inflation. However, an increase in deficit is found to be more inflationary and a decrease affects the inflation with a lower magnitude. The asymmetric impact of fiscal deficit on inflation can be explained through the existence of liquidity constraints, consumption-investment downward inflexibility and the downward price stickiness. Contractionary monetary policy action is found to be more effective than an expansionary one, signifying the asymmetric influence of monetary policy actions on the inflation of India. Similarly, in a supply-constrained economy with downward price rigidity, the authors found an asymmetric impact of output growth and output decline on inflation. As regard to the trade-openness, although an asymmetry is reported, the signs refute the validation of Romer (1993) hypothesis. Finally, the impact of oil price inflation on the inflationary pressures is according to theory but the coefficients are devoid of statistical significance.

These results indicate some important policy recommendations. Fiscal consolidation strategy should be executed in an appreciable manner to achieve the sound fiscal health and lower INF. The disciplined fiscal strategy would also be imperative for an effective monetary policy. Monetary authorities should possess noticeable credibility to manage the macroeconomic system and policy stances should be implemented according to requirements of the economy. Growth in output should be encouraged to have two-fold benefits to the economy – reducing INF on the one hand and fiscal deficits on the other.

The study contributes to the existing literature in the following ways. First, taking note of dynamic nature of the relationship between these two variables, the study examined the deficit INF nexus in a dynamic and asymmetric framework. The novelty of the study is ensured by the very nature of it is the first study in case of India to identify the fiscal INF in an asymmetric configuration. The authors applied a NARDL model, given by Shin et al. (2014) to examine the existence of any cointegrating relationship in an asymmetric paradigm. Second, the nature of causality between fiscal deficit and INF has been examined in a time domain and FD framework to portray precisely the casual interactions between these two variables in the short-run and long run. The study will, therefore, enrich the existing literature along the asymmetric lines.

Participants in leadership development programs take part in multiple developmental experiences that can influence the composition of their social network and enhance social capital. However, further investment in such practices may be limited because little is known about the relationship between leadership development approaches, networking ability, and social capital. This study explores how common developmental approaches may contribute to social capital, taking into consideration the role networking ability plays in this relationship. This descriptive, correlational study included a sample of graduates (N= 231) from 15 statewide agricultural-based leadership development programs. Our findings reveal that: 1) Networking is an antecedent to social capital, 2) skill building and personal growth approaches to leadership development are significant predictors of networking ability, and 3) networking ability is a significant predictor of social capital.