The Intrinsic Value of Valuable Paper: On the Infrastructural Work of Authentication Devices
Bibliographic record
Abstract
Authentication devices transform cheap paper into legitimate documents. They are the sensory, informational, and computational features that make up valuable papers like banknotes and passports, and they provide the confidence required in moments of exchange and passage. These devices – which include techniques like watermarks and specialized threads, proprietary substrates and inks, or RFID chips – are the product of security printing, an industry that continuously reinvents the possibilities of paper. Importantly, these components protect paper things from counterfeiting, allowing it to function as an original and authentic copy and to do the logistical work of connecting quotidian materials to global networks. The value of valuable papers is therefore not purely extrinsic, socially or discursively established, but is also performed through its intrinsic material qualities. These are the authentication devices that are read, assessed, and trusted as paper things are circulated, and they are what securely connects paper to infrastructures of mobility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.048 |
| Scholarly communication | 0.016 | 0.021 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".