Bibliographic record
Abstract
This exploratory essay foregrounds the extraction and enclosure cycle between education technology (ed-tech) vendors and public academic special collections and archives departments. Education technology vendors, subsidiaries of academic publishers, often approach special collections libraries and archives with offers to digitize collections through services that McLaughlin et al. (2023) describe as open wrapping or freemium proposals. Since there seems to be no turning back, information professionals in public academic settings should, among other solutions, encourage decision-makers to negotiate preservation and conservation of physical archival materials. Drawing from the literature on commons practices, this essay introduces the concept of reciprocal relations to agreements between cultural heritage institutions and ed-tech companies. A reciprocal approach would disrupt the extraction and enclosure cycle and highlights the professional’s role as a steward of cultural heritage collections with an understanding that digitization is not preservation. Further, it would compel private sector companies to invest in the public sector instead of simply extracting public resources for profit.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.030 |
| Scholarly communication | 0.018 | 0.024 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.032 | 0.011 |
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".