The Tourism-Migration Nexus: Towards a Theory of Global Human Mobility
Bibliographic record
Abstract
This paper argues that, despite multidisciplinary efforts, migration and tourism studies remain restricted by the paradigms to their own specialized industries: policy-relevant approaches geared towards government agencies and their fields of intervention in the case of migration studies as well as management perspectives directed to the expansion, marketing, and consumption of the travel industry in the case of tourism studies. The aim of this paper is to critique the trend of securitization in both fields of research and to hint at similarities in impact and meaning. Apart from the differentiation between consumption and production-led migration, both phenomena tourism and migration have a lot in common. Both are major driving forces of globalization and social change on the local level. By discussing recent critical literature on transnationalism, migration and tourism, this paper argues that hybrid forms of human mobility and the similar economic, environmental and social impact of tourists and migrants lead to the urgent reconfiguration of the social science paradigm through which the governance of human mobility is being studied. Ultimately, this paper wants to cross both perspectives and hint at similar issues of identity, social diversity, and sustainability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".