Bibliographic record
Abstract
Human identity and the meaning attached to being human have been shaped throughout human history by the entrenchment of new technologies and the cultivation of new human-technological relationships in life and society. This is particularly salient within contemporary society where the rise of digital culture and human enhancement technologies allow for human-technological relationships that directly challenge traditional conceptions of human nature and what it means to be human. New digital technologies and human enhancement technologies offer unique opportunities to improve the human condition by augmenting human abilities and practices in life and society. In response, a growing body of scholarly work focusing on the changing nature of human-technological relationships has nurtured in the emerging field of Technoself Studies (TSS). The purpose of this chapter is to trace the recent emergence of this new interdisciplinary field of research by exploring its conceptual development, important issues, and key areas of current technoself scholarship. The first part of this chapter provides a rationale, introduces key concepts, and presents a skeletal overview of key developments underlying Technoself Studies. The second part identifies key areas and issues in technoself research.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".