Bibliographic record
Abstract
The context: The exercise is part of an opening lecture in a course that addresses the interpretation of the “historical” books of the Hebrew Bible/Old Testament (the pedagogy works for any historiographic text). There are ten to twenty students, and we meet in a room small enough to allow us to hear each other. The pedagogical purpose: The exercise is intended to sensitize students to the limitations that characterize history writing. In particular, I want them to see the necessity and usefulness of selectivity, meaning the author's choice of some events and perspectives to the exclusion of others. An appreciation of the very selective nature of historical documents (primary and secondary sources) helps students interpret sympathetically the texts we study, and quickly illuminates the goal or ideology of the text in question in light of the choices made by its author. Description of the strategy: I ask the students to sketch a history of a recent day of their life in ten to fifteen minutes. To do so, they choose the most significant elements and place them in an organizational scheme or logic. There is no minimum or maximum number of main elements, but the time limit forces them to be selective. The choice of an organizational scheme is theirs to make, and I give them some ideas: a/chronological sequence, location, emotion, sphere (family, alone, friends), and so forth. Since history-writing is the imposition of meaningful order on a limited number of data, and since the result should represent faithfully something the author feels is important, the goal of their historical representation (there must be one!) may be anything they consider significant. Once their histories are done, each student explains her/his choice of data and organizational scheme in light of their goal. We focus on ways that selection or omission of data and choice of organizational scheme influence the overall presentation and help communicate the author's main point. Since some students usually know each other, we can often compare some “synoptic” perspectives on the same period or event along the way. The whole exercise takes 60-75 minutes. Why it is effective: It works because it is experiential learning. As they act the part of an author, students develop sympathy for an author's prerogative to choose material, perspective, and organization, and also grasp the link between these choices and the author's goal.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".