Job Insecurity: Coping, Conceptualization, and Dynamic Processes
Bibliographic record
Abstract
Given rapid technological advances, economic uncertainty, and volatile job markets, workers today are increasingly facing job insecurity. As a prominent work stressor, job insecurity has been found to have detrimental effects on employee job attitudes, well-being, and health. While these consequences are widely acknowledged, less is known about what actions employees can take to cope with job insecurity (reactive coping), how employees may proactively reduce their vulnerability to it (proactive coping), and whether job insecurity tends to diminish or escalate over time. The first two papers focus on reactive coping by examining the relationship between job insecurity and coping responses, namely falsifying work hours within the organization and searching for new jobs. They also explore the mediating mechanisms and boundary conditions. Shifting the focus from reactive to proactive approaches, the third paper investigates how job insecurity evolves over time and how proactive coping shapes this process. Extending the previous unidimensional conceptualization, the fourth paper distinguishes between qualitative and quantitative job insecurity. It examines why and when qualitative job insecurity may escalate into quantitative job insecurity. The four papers included in this symposium draw upon various theoretical perspectives (i.e., conservation of resources, self-regulation, and adaptation theories), employ rigorous research designs (i.e., meta-analytic, time-lagged, and longitudinal designs), and use diverse samples (samples from Australia, China, the US, and New Zealand). We hope this symposium can enrich the understanding of how employees cope with job insecurity as well as the conceptual frameworks and dynamic processes surrounding job insecurity, paving the way for future research on this topic. Job Insecurity, Covert Competition, and Falsifying Work Hours: The Role of Zhongyong Beliefs Author: Xizhi Liu; The Chinese University of Hong Kong, Shenzhen Author: Xiaomin Xu; The Chinese University of Hong Kong, Shenzhen Author: Mengyuan Wang; Xi'an Jiaotong-Liverpool University Job Insecurity: How A Boundaryless Mindset Shapes Its Influence on Territoriality and Job Search Author: Xingwen Chen; Fudan University Author: Cynthia Lee; Northeastern University Author: Guohua (Emily) Huang; Hong Kong Baptist University Understanding Job Insecurity Over Time: The Role of Future-Oriented Planning Author: Yan Tu; Central China Normal University Author: Lixin Jiang; The University of Auckland When it Rains, it Pours: From Qualitative Job Insecurity to Quantitative Job Insecurity Author: Lixin Jiang; The University of Auckland Author: Xiaowen Hu; Queensland University of Technology Author: Maike Debus; University of Neuchâtel Author: Sergio López Bohle; Author: Laura Petitta; Sapienza University of Rome Author: Lara Christina Roll; PricewaterhouseCoopers Belgium BV/SRL Author: Marius Stander; North-West University Author: Hai-Jiang Wang; Huazhong University of Science and Technology
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".