Bibliographic record
Abstract
This paper is based on a presentation I gave at the Access Conference in Toronto, Ontario on September 10th, 2015. Both the presentation and this paper are explorations in three parts. The first part is a short history lesson on the use of paper cards by scholars and librarians, which led to the introduction of the “Scholar’s Box.” The second part asks the question: Can we consider Zotero as the Scholar’s Box of the digital age when it cannot capture important metadata such as linked open data? It is recognized that this is not just a shortcoming of Zotero: research is surprisingly still very difficult to share between scholars, libraries, and writing tools. This is due to an inability to capture the “invisible text” when we copy and paste citations from one application to another. The third part establishes that the digital card is now the dominant design pattern of web and mobile, and notes that these systems are largely restricted to proprietary platforms, which restricts the movement of cards between systems. This paper then suggests how we might transform the historical Scholar’s Box, by using HTML5 index cards from Cardstack.io as a means to bring new forms of sharing on the web, and, in doing so, reconnect the scholar to the library. Cet article est basé sur un exposé que j’ai donné à Access Conference à Toronto le 10 septembre 2015. L’exposé et cet article sont des explorations en trois parties. La première partie est une leçon d’histoire courte sur l’usage des cartes en papier par les spécialistes et les bibliothécaires, qui a mené à l’introduction du “Scholar’s Box”. La seconde partie pose la question: Est-ce que nous pouvons considérer Zotero comme le “Scholar’s Box” de l’âge numérique, même s’il ne peut pas capturer des métadonnées importantes telles que les données liées ouvertes? On reconnaît que ce n’est pas seulement une lacune de Zotero: étonnement, la recherche est toujours très difficile à partager entre spécialistes, bibliothèques, et outils d’aide à la rédaction. Ceci est dû à l’incapacité de capturer le “texte invisible” quand on copie et colle des citations d’une application à une autre. La troisième partie établit que la carte numérique est maintenant le motif dominant sur le Web et sur le mobile, et constate que ces systèmes sont largement limités aux plateformes propriétaires, ce qui limite le mouvement des cartes entre les systèmes. Cet article suggère comment on pourrait transformer le “Scholar’s Box” historique en utilisant les cartes d’index HTML5 de Cardstack.io comme moyen d’apporter de nouveaux moyens de partager sur le Web, et ce faisant, reconnecter le spécialiste à la bibliothèque.
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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.029 | 0.026 |
| Scholarly communication | 0.040 | 0.039 |
| Open science | 0.003 | 0.028 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.037 | 0.012 |
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".