Bibliographic record
Abstract
This article is an experiment in constructing a new form of narrative through the history of Mozambique. It assembles photographic images of a specific physical structure, the bridge, dating from the colonial period to the contemporary. Thus it follows instances of the making (and unmaking) of bridges as lines of infrastructure, or form, photographed, as these cross the riverine features in the land in order to facilitate connection, traffic, and progress. Great rivers such as the Zambezi flow in one direction, which has also served as a metaphor for the gradual passing of time. In such a case, the bridge cuts across the river at right angles to make mobility and speed possible, inserting new temporalities and spatial transitions. But whether through war, the folly of out-of-scale ambition, or corruption, progress always seems to be on the other side of the river and time seems to move slowly again. Here we work with the propensity of the photograph to disturb expectations of sequential and chronological narrative, its ‘vertical sampling’, to quote Elizabeth Edwards, that distributes the possible parts of any historical reconstruction in unexpected ways. Because of the way a photograph compresses space and time, it renders the space in front of the camera as a detailed micro view and offers a shift in scale. When one attempts to fold photographs into larger historical narratives, they tend to produce sequences that appear temporally askew and lead in different disciplinary directions whose references might traverse poetry, political economy, history, cinema, anthropology, and critical theory. If modernity is fast and its antinomy is slow, most Mozambicans must navigate some kind of synthesis or mode of survival that constantly throws into question the very notion of progress itself.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".