Not All Who Wander Are Lost: Redefining Career Exploration and Indecision in Undergraduate Students
Bibliographic record
Abstract
Inspired by a Tolkien quote, “Not All Who Wander Are Lost,” the authors introduce the concept of career wandering in the context of undergraduate student development. Proposing an alternative to traditional linear career trajectories, we conceptualize a dynamic approach that embraces nonlinear paths, indecision, and adaptability in a rapidly changing labor market. Drawing from our experience as educators, we define career wandering by integrating principles of lifelong learning, flexibility, chance events, and openness to diverse experiences. We explore the implications of career wandering for student affairs professionals, emphasizing the need for supportive, inclusive environments that encourage exploration and holistic student development. Addressing potential critiques, we acknowledge the challenges of equity and accessibility, and the need for intentional institutional support. Ultimately, the career wandering approach aligns with the evolving nature of work and promotes a more inclusive and adaptable model of career development in higher education.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.023 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".