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
This paper advances the conceptualisation and application of intellectual capital, a key concept in the intellectual migration framework, to understand international student mobility. The intellectual migration framework contends that higher-education and highly-skilled migrants acquire, upgrade and utilise intellectual capital for upward career and social mobility. This paper argues that intellectual capital is not the sum of different forms of capitals, but a complete package with human, cultural and social capitals working in synergy through the agency of migrants. Focusing on higher-education students at the beginning of the intellectual migration continuum, it analyzes how intellectual capital is differentially accumulated at various stages of the educational process. Drawing on 51 semi-structured interviews with Chinese international students in North America, we learn that pre-migration intellectual capital, due largely to parents and family, reflects social inequality in contemporary societies whereas that obtained while studying abroad reveals more on individual agency. As such, intellectual capital accumulation abroad serves as a mediating process, especially for those with less privileged backgrounds. Supportive international higher education sectors in both sending and receiving countries can also assist students in their intellectual capital cultivation process and contribute to alleviating educational inequality.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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