ABSTRACT Documentary analysis brings together judgements about source content, claim readiness, downstream use and reportable conclusions. This article presents a source‐traceable procedure that assigns these judgements to distinct analytic objects and connects them through explicit handoffs. Four functional statuses characterize fixed source spans; a condition‐based control records whether a proposed claim is released, qualified, held or withdrawn. Source support and reporting permission remain separately inspectable. Public Horizon records provide a designer‐applied worked demonstration, whereas State v. Loomis provides a sanity check on two established use boundaries. A hypothetical contrast on one Horizon object makes the integration visible: An aggregate statement can remain reportable, whereas an individual‐level promotion is held and a boundary‐crossing inquiry remains unresolved. The article also specifies a prospective independent‐coder study of the functional instrument. Together, the codebook, source manifest and evaluation design provide an operational specification for inspection, reapplication, and subsequent testing.
Elementary school entry is one of the earliest and most significant educational transitions, yet research has largely reduced it to a matter of school readiness and adaptation. This qualitative study implemented a play-based activity to support five-year-old children’s transition to elementary school and explored how the participating children experienced and constructed their peer relationships and perceptions of school. The activity was conducted in collaboration with first-grade children and teachers from a nearby elementary school over eight fortnightly sessions from September to December 2023, and all 13 five-year-old children in the class took part in every session. Interviews with the children, first-grade children, teachers, and parents, together with participant observation records collected across the sessions, were analyzed using reflexive thematic analysis. Three themes were constructed: the children moved from unfamiliar encounters to the formation of meaningful relationships; from an image of school to imagining the “self” within school; and they began to participate in the ways of the school community. The findings suggest that the transition to elementary school is better understood not as a matter of improving an individual child’s readiness but as a process in which relationships and information accumulate through collaboration with elementary school children and teachers.
This study examines the associations among transformational leadership, emotional labor strategies, self-efficacy, and job-related well-being among 355 employees of a Turkish insurance company. Drawing on Social Cognitive Theory and Conservation of Resources Theory, data were collected using convenience sampling and analyzed with SPSS 22 and SmartPLS 4. The findings indicate that transformational leadership is not significantly associated with deep acting but is negatively associated with surface acting. Both deep acting and surface acting are significantly associated with self-efficacy, which is strongly positively associated with job-related well-being. The results also reveal a significant serial indirect association linking transformational leadership, surface acting, self-efficacy, and job-related well-being, whereas the corresponding pathway involving deep acting is not significant. Self-efficacy further appears to mediate the associations between emotional labor strategies and job-related well-being. Participants’ specific job functions and levels of customer contact were not recorded; therefore, the findings should not be interpreted as specific to customer-facing roles. Overall, these findings challenge the assumption that transformational leadership is uniformly associated with positive emotional labor strategies and offer a more nuanced understanding of the associations among leadership, emotional labor, and employee well-being.
Artificial intelligence (AI) is increasingly embedded in organizational work, yet its implications for employee work well-being remain unclear. Integrating Job Demands–Resources (JD–R) theory with organizational support theory, cognitive appraisal theory, and social information processing theory, this study used a two-wave, single-source questionnaire design to examine two pathways linking employee–AI collaboration to work well-being and the moderating role of leader AI symbolization (LAIS). Data from 335 employees in China showed a positive total association between employee–AI collaboration and work well-being. Employee–AI collaboration was positively associated with both AI-related perceived organizational support (AI-related POS) and workload: AI-related POS carried a positive indirect effect, whereas workload carried a negative indirect effect. Because these pathways operated in opposite directions, their summed indirect effect was not statistically significant. LAIS strengthened the AI-related POS pathway and attenuated the workload pathway. Simultaneous path analysis and bootstrap robustness tests yielded the same pattern. These findings characterize employee–AI collaboration as a work arrangement that may be appraised through both resource-gain and demand-related pathways; the two-wave design does not establish causal ordering.
The proliferation of generative AI tools in educational settings raises a fundamental but underexplored question: does delegating creative teaching tasks to AI erode the psychological rewards that make teaching meaningful? In the current research, we advance a dual-level framework distinguishing the immediate emotional costs of AI involvement at the task level from its broader costs at the career level. We tested this framework across two complementary studies. Study 1 was a randomized experiment (N = 101 high school teachers) where participants either designed a classroom activity independently or revised an AI-generated draft. Teachers who revised the AI-generated draft reported lower psychological ownership of the product, which partially accounted for their lower state pride; this indirect effect was stronger among teachers with stronger callings. Study 2 was a two-wave time-lagged field survey (N = 231 university teachers) examining habitual AI involvement and career calling at Time 1 and psychological ownership and work meaningfulness one month later. AI involvement was indirectly associated with lower work meaningfulness through lower psychological ownership, with the indirect effect stronger among teachers with stronger callings. Together, the two studies provide experimental (Study 1) and time-lagged correlational (Study 2) evidence that AI involvement is associated with lower psychological ownership, which in turn is linked to lower pride in a specific task and lower meaningfulness of work as a whole. These associations were stronger among teachers with stronger callings, suggesting an ironic vulnerability that warrants attention in educational AI policy, teacher professional development, and AI system design.
