Career studies in search of theory: the rise and rise of concepts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose – The purpose of this paper is to introduce further clarity to career scholarship and to support the development of career studies by complementing earlier theoretical literature reviews with an evidence-based historical analysis of career-related terms. Design/methodology/approach – Data from 12 career scholars were collected using the historical Delphi method to find consensus on the career terms that have shaped career studies between 1990 and 2012. The authors then explored the literature by collecting data on the occurrence of these terms, analyzing frequencies and trends via citations and indexes of citation using a mixed-method combination of historical literature review and performance analysis. Findings – Career scholarship is indeed a descriptive field, in which metaphors dominate the discipline. Career success and employability are basic terms within the field. The discipline tends to focus narrowly on career agents. There is a plethora of terminology, and, contrary to the expectations, concepts introduced tend not to fade away. Originality/value – The authors offer an overarching perspective of the field with a novel mixed-method analysis which is useful for theory development and will help unify career studies. Earlier comprehensive literature reviews were mostly based on theoretical reasoning or qualitative data. The authors complement them with results based on quantitative data. Lastly, the authors identify new research directions for the career scholarship community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it