Browsing by Subject "recruitment"

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    Examining personality assessment in asynchronous video interviews (AVI): convergence between human personality judgements and AI/ML scoring
    (2025) Cronje, Jacobus Fouche; de Kock, Francois
    The assessment of personality is an essential component of personnel selection due to its validity in predicting job performance. To assess personality, asynchronous video interviews (AVIs) scored using artificial intelligence (AI) algorithms are increasingly used, allowing candidates to record responses to interview prompts that are subsequently evaluated automatically by AI algorithms and/or human raters. As questions remain about the validity of AI-based AVI scoring approaches, this study examines the convergence between human-and AI-scored personality assessments. To measure personality, the study focuses on the HEXACO model, which measures Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness to Experience. Verbal responses were transcribed from videotaped AVIs of 161 mock interview candidates who answered five AVI questions. Responses were scored by 15 trained human raters and a closed-dictionary text-analysis keyword-counting AI algorithm developed for this study, respectively. The correlation between trait-level scores produced by human judges and AI scoring was tested both across traits and within traits (trait-level) to assess scoring convergence. Moreover, in addition to comparing score levels produced by the two scoring methods (AI vs. human raters), score spread (i.e., variability), rank-order stability, and rating reliability were evaluated. The findings revealed a moderately positive and significant overall convergence (r = .29, p < .001) across traits between human and AI evaluations, which suggests that AI scoring may potentially be useful as a replacement of human evaluations when general screening is desired. Trait-level convergence varied between scoring methods, with the scoring consensus between human raters and AI being higher for some traits than for others, suggesting that these methods rely on different information and/or may interpret interview responses differently. The research highlights the potential of AI to complement human- based scoring of AVIs used in recruitment, selection, and assessment while also identifying the limitations of algorithm-based scoring in capturing complex human behaviour in interviews. The findings may further contribute to understanding the role of AI in personality assessment and implications for organisational practices.
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    Fisheries management under climate and environmental uncertainty: control rules and performance simulation
    (Oxford University Press, 2014) Punt, Andre´ E; A’mar, Teresa; Bond, Nicholas A; Butterworth, Doug S; de Moor, Carryn L; De Oliveira, Jose´ A A; Haltuch, Melissa A; Hollowed, Anne B; Szuwalski, Cody
    The ability of management strategies to achieve the fishery management goals are impacted by environmental variation and, therefore, also by global climate change. Management strategies can be modified to use environmental data using the “dynamic B0” concept, and changing the set of years used to define biomass reference points. Two approaches have been developed to apply management strategy evaluation to evaluate the impact of environmental variation on the performance of management strategies. The “mechanistic approach” estimates the relationship between the environment and elements of the population dynamics of the fished species and makes predictions for population trends using the outputs from global climate models. In contrast, the “empirical approach” examines possible broad scenarios without explicitly identifying mechanisms. Many reviewed studies have found that modifying management strategies to include environmental factors does not improve the ability to achieve management goals much, if at all, and only if the manner in which these factors drive the system is well known. As such, until the skill of stock projection models improves, it seems more appropriate to consider the implications of plausible broad forecasts related to how biological parameters may change in the future as a way to assess the robustness of management strategies, rather than attempting specific predictions per se.
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    The Evolutionary Ecology of Sprouting in Woody Plants
    (2003) Bond, William J; Midgley, Jeremy J
    Woody plants may be killed by severe disturbance or resprout from vegetative tissue. Sprouters can persist at a site through several generations of nonsprouters. Differences in sprouting behavior are therefore important for understanding vegetation dynamics, extinction risks, and woody plant management. Although sprouting appears not to be uniquely correlated with many other intrinsic attributes, such as specific leaf area or breeding systems, a clear correlate is reduced seedling aboveground growth rates from sprouters allocating more to belowground structures. Consequently, sprouters tend to have low seedling recruitment rates, and saplings take longer to reach maturity. Sprouters also tend to have lower seed output than nonsprouters, but comparative studies have seldom taken other trait differences such as plant size into account. Added to these trade-offs between persistence and recruitment, sprouters are often multi stemmed and shorter than related nonsprouters and may be outcompeted by them when disturbances are rare. Since sprouters tend to have long generation times, damped demographic trends, and gene flow across generations, it has been suggested that their speciation rates would be low. The available data, primarily from fire-prone Gondwanan shrublands in South Africa, show no strong differences in speciation rates of related sprouters versus seeders. This indicates that ecological factors are important determinants of the evolution of fire life