Mapping infrastructural encounters: an analysis of skilled migrancy in Australia and Canada
Bibliographic record
Abstract
This thesis argues for a new research agenda that begins by “mapping” when, where, and how skilled migration infrastructure is experienced and navigated by immigrants. It explores experiences of “skilled migrancy” as a perspective that focuses on the agentive potential of migrants in dictating and designing their mobile trajectories. This study builds upon the recent ‘infrastructural turn’ in migration studies, which has provided valuable insights into the emergence and functions of the different aspects of migration infrastructure (i.e., commercial, social, technological, regulatory and humanitarian) (Xiang and Lindquist, 2014). Empirical studies on migration infrastructure have predominantly focused on exploring processes involved in informal and semi-formal labour migration. There is a scarcity of literature that examines formal skilled migration, which is a type of labour migration distinguished by its specific qualities regarding how “skill” is assessed, evaluated and perceived by both policy frameworks and migrant groups. There remains a further and related gap in exploring the multiplicity of infrastructural processes within singular migration trajectories, which hinders the capacity to understand holistically the lived experience of contemporary migration. My thesis aims to address both these gaps. This thesis introduces the concept of “infrastructural encounter” to explore specifically the relational dynamics between skilled individuals and what I have framed as “skilled migration infrastructure”. Showcasing migrant case studies from Australia and Canada, two popular skilled immigration destinations, the empirical analysis identifies three relational frames or “sets of relationships” between migrants and skilled migration infrastructure. The first set of relationships demonstrates the ways in which skill is constructed, negotiated and redefined through infrastructural encounters rather than being a static classification for migration as defined by policy frameworks. The second set of relationships explores the temporal dynamics of infrastructural encounters and the ways in which they shape or direct migrants’ desire for skilled mobility over time. The final relational frame delves into the affective and emotional potentialities of infrastructural encounters and the ways in which they influence skilled immigrant experiences. In presenting these relational frames, this thesis argues that rather than simply being facilitated or constrained by migration infrastructure, contemporary skilled mobility is shaped by infrastructural encounters, or the relational and two-way interactions between immigrants and skilled migration infrastructure. These interactions embed within them negotiations, considerations, desires, and emotions that are fluid, mobile, and constantly evolving across time and space. This research contributes to migration scholarship, specifically to the continuing academic focus on migration infrastructure by providing nuanced understandings on how it is experienced in the context of skilled mobility. In doing so, it also responds to the call for more critical examinations of the notion of skill by understanding it from the migrants’ perspective.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.022 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".