Bibliographic record
Abstract
Volume XX (Spring 2011) of Frontiers: The Interdisciplinary Journal of Study Abroad takes a thematic focus on “Study Abroad and the City.” As part of the Global Cities Seminar hosted by CAPA International Education in Vancouver in May 2011, participants were asked to consider the use of the city as text, the city as document, and the city as cultural informant. The articles featured in the journal and at the workshop presented an array of case studies and compelling arguments for ensuring active engagement with the physical environment that various urban spaces provide as educative tools for students abroad. During the discussion that followed the presentations, an aspect not fully explored either in the journal or on the panel occurred to me. What about the city as a relationship? As Rodríguez and Rink suggest in their article Performing the City: Engaging the High Tech Flaneur (2011), the ability of the city to elicit a visceral and emotional response is a powerful but often untapped element of the experience abroad. At the most obvious and basic level, travelers inevitably articulate their experience of destinations in the language of emotion: “I did not really like Venice, but I loved Rome.” I would like to give a bit of consideration to the emotional relationship travelers, and more specifically students on programs abroad, have with cities. I would also like to suggest some of the opportunities “the city as relationship” might offer if explored or presented as such.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.004 |
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".