Social Symbolic Work Through a Temporal Lens: Understanding the Interplay of Agency and Temporality
Bibliographic record
Abstract
In organizational studies, the concept of ‘work’ has evolved to encompass diverse streams, such as institutional work, identity work, or emotion work, recently brought together through the framework of social-symbolic work. Recent work shows how actors use time as a resource, structure, and process, offering tools to analyze how temporality influences the creation, maintenance, and change of social-symbolic objects across contexts. The purpose of this panel symposium is to explore the intricate relationship between temporality and social-symbolic work in organizational contexts, providing a better understanding of how past, present, and future orientations shape organizational processes. Distinguished scholars will investigate how actors purposefully create, maintain, and transform social-symbolic objects through complex temporal interactions. Further, the panel will critically assess current findings and bridge fragmented research areas. Participants will explore three key dimensions: (1) the dynamic and relational nature of social-symbolic objects, (2) emotions as temporal forces in organizational work, and (3) ontological perspectives on temporality. By fostering an interactive dialogue, this symposium aims to develop a more nuanced understanding of how temporal dimensions shape organizational work, offer new insights into the relationship between agency and structure, and articulate promising future research directions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.049 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".