Bibliographic record
Abstract
This article integrates William James’ (1890) theoretical model of Self with contemporary theoretical discourse and recent research on the impact of digital technology upon the Self. An overview of James’ self-theory is presented and followed by a detailed review of contemporary publications on self in our increasingly digital world; organized around the Spiritual, Social and Material realms of James’ “Me”. This is followed by this author’s extension of James’ concept of “I” into contemporary discourse on the person in terms of authenticity, agency and power. It is shown that the “Spiritual Self” is reflected in technology as fragmented, decentred and dislocated while the “Social Self” has expanded into virtual communities; continuing to seek recognition from others, but in a magnified and accelerated fashion. A cultural shift has been identified towards one of simulation and surveillance. Transformations of the “Material Self” in terms of physical bodies, interaction with the material world, and with material others, are presently observed. This author’s conceptual and theoretical exploration has also shown a corresponding loss of control and fracturing of the status of the person through the rise of surveillance and loss of personal rights that challenges the theoretical construct and everyday experience of persons.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".