Inquality and the Future of Global History: A Round Table Discussion
Bibliographic record
Abstract
The following is an edited transcript of a roundtable that took place at the University of Glasgow in September 2018. The roundtable was organized by Dr. Julia McClure in conjunction with the Poverty Research Network’s conference - Beyond Development: The Local Visions of Global Poverty. That conference brought into focus the ways in which the global and local levels meet at the site of poverty and highlighted the different conceptions on the global are generated from the perspective of poverty. The roundtable brought together leading scholars from Europe, Africa, Asia and North and South America to take stock of global history as a field, to consider the role of existing centres of knowledge production, and to assess new directions for the field.
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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 | 0.028 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.020 | 0.022 |
| Scholarly communication | 0.041 | 0.043 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.020 | 0.030 |
| Insufficient payload (model declined to judge) | 0.028 | 0.002 |
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".