Thinking skills and the context of higher education teaching today. What is known
Bibliographic record
Abstract
A time to think Each of us can surely testify to the tidal wave of change sweeping through not only higher education, but all aspects of society, bringing with it a need to change the ways in which we think, learn and communicate. These changes signal a transformation in the very nature of the job market (Naisbitt & Aburdene, 2000) for the students we teach and are reflected in the requirement for creative, self-acting managers in the professions in which they will soon find themselves. A digital economy heralds the beginning of an “age of networked intelligence” (Tapscott, 1998) with its demand for immediacy and for instant communication. Whether we like it or not, we are now living in an age of choice and decision-making. The ability to think is being viewed as an employability skill for an increasingly wide range of jobs, and as a requirement for responsible citizens in a democratic society, and for many typifies what we, in higher education, might recognise as an educated person.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".