Skill as a relational construct: hiring practices from the standpoint of Chinese immigrant engineers in Canada
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
Under-employment and unemployment of immigrants has often been attributed to immigrants’ lack of human capital skills and/or cultural and social capital endowments. Few studies have addressed the fact that despite these possible ‘capital’ disadvantages, immigrant niches are occasionally made in professional fields. Based on an institutional ethnographic study, this article sheds light on this phenomenon. Specifically, it traces some of the hiring practices found within the engineering profession in Canada from the standpoint of Chinese immigrant engineers. It unveils a hard versus soft skill discourse that ideologically relegates minoritized immigrants to the bottom of the hiring queue. It also maps a project-based and network-dependent hiring schema that paradoxically renders immigrants without ‘desirable’ skills simultaneously dismissible and indispensable. It further argues that the skill discourse revealed constitutes a rationalizing mechanism through which racialization and capitalist pursuit of maximum surplus value interact to produce differential opportunities for immigrants at different places and times.
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 | 0.000 | 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