Bibliographic record
Abstract
The term “translation” shows up in myriad sites within and outside of academia. It is frequently used to explain processes of movement and connection between languages, places, contexts, and ideas. Despite this ubiquity, translation as a concept is undertheorized within social science academic discourse. This paper responds to this gap by epistemologically rethinking translation and arguing that translation is emergent and geographic. The practices, processes, and politics of translation, therefore, can generate conditions for social transformation, which can lead to co-liberation. With this in mind, we draw on ideas of “improvisation,” “accompaniment,” and “emergent strategy” to conceptualize our rethinking of translation. We illustrate the possibilities of our rethinking by tracing translation within and through the Race and Social Justice Initiative (RSJI) in Seattle, Washington, a municipal government-led endeavor to eliminate institutional racism and race-based disparities. Situating translation as emergent and geographic shifts attention to the ways and contexts through which possibilities for social change emerge in time and place. Thus, our theorizing of translation has broad utility for critical geographic inquiry and the specific study and praxis of local scale policy-making and governance.
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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 | 0.139 | 0.191 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.017 | 0.084 |
| Scholarly communication | 0.026 | 0.042 |
| Open science | 0.006 | 0.025 |
| Research integrity | 0.011 | 0.021 |
| Insufficient payload (model declined to judge) | 0.008 | 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".