Bibliographic record
Abstract
It seems fitting that the recursive, iterative and circulatory dynamics of mediation at the heart of this anthology are matched in pace and connectivity by the processes that brought it to fruition.The project has advanced haltingly but collaboratively over the course of many years, taking a multiplicity of forms and interpellating a number of audiences and participants along the way.Our editorial efforts, moreover, have been matched unevenly by the rapid tempo of the unfolding "migrant crisis," a temporality that made various forms of analysis impossible, even as it pushed us to generate new modes of thinking and academic engagement.Some of our initial thinking was incubated at the Hemispheric Institute's Encuentro in 2014 in Montréal / Tio'tiá:ke, which helped f lesh out the possibilities and limitations of the concept "trespass" (a modality for us to think bodily crossings and mediated borders).We are grateful also to participants in a workshop at the National Women's Studies Association Annual Conference in 2016 that sought to critically examine the representational regimes that frame and instantiate the European "migrant / refugee crisis" and consider the decolonizing potentials of various strategies of counter-mapping, critical reading, and collaborative knowledge production.The anthology would not have been possible without the generous and generative participation of Farah Atoui,
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.403 | 0.271 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".