Facilitating Life-Enhancing Career in the Context of Significant Social Challenges and Changes: The Perspective of Goal-Directed Action
Bibliographic record
Abstract
The problems and challenges people in both Eastern and Western societies face regarding life work and career are complex and in flux. These issues range from a neoliberal socio-economic climate to the increasing prevalence of the gig economy and part-time work. These problems, compounded by racism and social injustice, threaten the existential and moral commitment required not only for sustained work involvement but also for constructing a meaningful life. The neoliberal agenda appears to give pre-eminence to individual agency. However, at the same time, it challenges the joint collaborative and cooperative requirements needed to construct meaningful long-term carreers. These challenges to long-term career are elaborated. In this article, we address this problem by examining the conceptual link between short-term, goal-directed actions, mid-term projects and long-term career, in an approach known as contextual action theory. Essentially, this framework suggests that long-term career is constructed through in-the-moment goal-directed actions and mid-term projects, both of which require significant components to contribute to a meaningful and motivated career. This article provides the opportunity to examine the characteristics of contextual action theory that contribute to addressing the challenges to long term career, including goals as explanatory, relation to the other, the process of change, culture, and social justice. These characteristics are illustrated by referring to current research and practice that have emerged from contextual action theory.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.032 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".