Valdosta State University

Problem: Learning is extensively recognized as central to HRD, but no comprehensive, evidence-based synthesis has mapped how learning scholarship has evolved over the last two decades – its intellectual structure and thematic shifts. Solution: We examined the scholarly landscape of learning-related AHRD-sponsored articles using bibliometric analysis and topic modeling, analyzing 490 peer-reviewed articles published between 2005 and 2024. Bibliometric analysis identified publication characteristics and annual production patterns, examined influential sources and collaboration networks, and mapped relationships among cited references, authors, and keywords. Topic modeling yielded 12 distinct topics capturing major learningrelated themes. A time-series analysis classified topics as “Hot” or “Cold,” indicating areas of increasing or decreasing scholarly attention over time. Stakeholders: The study offers actionable implications for HRD researchers and practitioners to support evidence-based learning strategies and strengthen learning climates in organizations. For HRD leaders and policymakers, the findings provide an empirical basis for aligning learning investments with workplace priorities and targeting evidence-informed interventions.

With the more pronounced infusion of artificial intelligence (AI) into public sector operations, there exist a host of ethical concerns that arise pertaining to how public sector organizations make decisions about workflow and the automation of processes, bureaucratic accountability, and sustaining democratic governance and transparency. Through the lens of institutional ethics, this article explores the morality of using AI as a tool in government and how an increased reliance on stronger AI approaches presents heightened ethical and practical blind spots that have significant ramifications for sustaining the public trust. In considering recent AI initiatives at the national level, we argue that pre-existing codes of ethics, which are framed around the theoretical genre of institutional ethics, must evolve coterminously as AI becomes more integrated as a tool in government. We explore trends for the two most recent presidential administrations, using the AI national strategies from both to focus upon two primary areas of consideration relating to institutional ethics: first involves the ethical considerations relating to work completion and processes that emerge from deeper and stronger integration of AI tools in public sector organizations; and second reflects upon bureaucratic accountability as AI tools change the nature of responsibility and decision-making.

To the Editor: We read with great interest the report by Sassine et al. describing the incidence and outcomes of infants with cancer in Canada, with comparative analyses between neonates (0 to <30 days) and older infants (30 days to <1 year) [1]. The authors demonstrated clinically meaningful differences in cancer distributions and survival across these age strata. To further quantify the underlying biological pattern, we examined the published cancer-type distributions through the lens of Shannon entropy, a well-established measure of distributional diversity [2]. The increase in diversity was driven primarily by greater representation of retinoblastoma, acute lymphoblastic leukemia, and nephroblastoma in older infants (Figure 1B). Conversely, the predominance of malignant extracranial germ-cell cancers in neonates, together with relative declines in myelodysplastic/myeloproliferative disorders, acted to dampen—but not eliminate—the overall increase in entropy. These findings are consistent with a shift from a concentrated, largely embryonal cancer spectrum at birth toward a more heterogeneous distribution that increasingly includes hematologic, renal, and neuro-oncologic malignancies later in infancy. Although the entropy used here is informational [2] rather than thermodynamic [3], the conceptual analogy is noteworthy: increasing entropy in this context reflects diversification of oncogenic processes across early developmental windows. Importantly, this approach does not replace conventional epidemiological metrics [4], but instead offers a compact, quantitative framework for summarizing complex distributions and identifying specific categories responsible for observed shifts. Our analysis complements the work of Sassine et al. by demonstrating that differences in cancer distribution across early infancy are not merely qualitative, but are quantitatively coherent when viewed through the lens of Shannon entropy. Future applications might include longitudinal comparisons beyond the first year of life, cross-country analyses, and integration with molecular features to assess whether increasing phenotypic diversity parallels increasing genetic heterogeneity. We thank the authors for generating a valuable dataset and for stimulating new perspectives on infant cancer biology. The author declares no conflicts of interest. Supporting Information Table S1 Numerical data and processing steps. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

This article explores how a collaborative inquiry into feeling’s role in evolving collaborative creativity adapted sonopoetic methods for analyzing affective aspects of experiencing. Following feelings coauthors experienced in/with/through our practice of experimenting and playing with sounds, we enacted sonopoetic methods for analyzing our multimodal data and presenting findings. In the process, we discovered ourselves cultivating posthumanist subjectivities inclusive of more-than-human figures, animal beings, and digital technologies. The inquiry produced a series of research poems to performatively enact our research process and present findings in affective ways. The three research poems included in this article pursue conceptual clarity among affect, feeling, and felt sense and explore implications for how affective aesthetic knowing potentially leads to different and/or wider ways of becoming, thinking, and doing.

Purpose Perceived job security is positively associated with employee and organizational outcomes, yet antecedents to perceived job security remain understudied. Drawing on signaling theory, this study examines how family-supportive supervisor behaviors (FSSBs) influence employee perceptions of job security and the role interpersonal trust plays. Design/methodology/approach To test the hypothesized model, the authors utilized a two-wave study design of working adults in the U.S. (n = 165), analyzing the data using PROCESS Macro model 4. Findings All four dimensions of FSSB (emotional support, instrumental support, role modeling, and creative work-family management) and overall FSSB are positively associated with employee-perceived job security directly and indirectly through affect-based trust. Cognition-based trust fully mediates the relationships between emotional support, instrumental support and perceived job security, partially mediating the relationships among role modeling, creative work-family management, overall FSSB and perceived job security. Originality/value The perceived job security literature is extended to explore antecedents and illustrate how FSSBs, along with trust, positively influence employee-perceived job security.