GenAI on GenAI: Two Prompts for a Position Paper on What Educators Need to Know
Bibliographic record
Abstract
This paper outlines and critically analyzes the process, expectations, and outputs of a ChatGPT search on what educators need to know about GenAI. The paper includes two versions of a prompted position paper generated by the free OpenAI tool ChatGPT 3.5. The prompt and the resulting paper(s) are identified as parallel, in content, to an educational video script on AI itself, whose creation the author has recently supervised. However, the content of the generated position paper(s) – while somewhat surface – turns out to be less problematic than the format, in spite of direct format-oriented prompting. This outcome and the implications of both content and format issues for the field of higher education are discussed in the reflection. The overall conclusion is that GenAI should be a site of critical literacy development, while broader concerns about the impacts of these tools on knowledge and society must also be foregrounded. (This abstract was written by the human author.)
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".