Can the University Escape From the Labyrinth of Technology? Part 2: Intellectual Map-Making and the Tension Between Breadth and Depth
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This second part continues the search for ways of overcoming the three limitations of the current intellectual and professional division of labor and its knowledge infrastructure, which were shown to be at the root of the present economic, social and environmental crises. A complementary knowledge strategy is proposed to counterbalance the trade of breadth for depth, based on the creation of intellectual maps. One such map is described for engineering, showing how through the process of industrialization people change technology and how through its influence on human life and society, technology changes people. Because industrialization cannot destroy the matter and energy it requires, it also transforms its relations with the biosphere. Once the connections between technology and everything else are mapped, specialists can inquire into the consequences of their design and decision making that fall beyond their domains of expertise, to introduce a preventive orientation into their work to achieve a better ratio of desired to undesired effects. This is shown for materials and production, energy, work, and cities. In subsequent parts, it will become apparent that this example is paradigmatic for other professions, the social sciences, and the university.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.003 | 0.089 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it