Bibliographic record
Abstract
Traditions of cultural life furnish numerous avenues to suffering; the challenge is to develop resources for moving through cultural life effectively as opposed to sedating ourselves for the journey. (K. J. Gergen, 2006: 159) Our words constitute forms of action that invite others into certain forms of relationship as opposed to others. (M. M. Gergen and K. J. Gergen, 2001: 13) Psychology has been the source of many ideas and interventions when it comes to professional practice. A major fork in the road occurred early in the discipline's history when most psychologists decided on a natural science over human science direction. This shift saw most psychologists aiming to explain human experience using methods and ideas one associates with the ‘hard sciences’: statistical prediction, ‘objectivity’ and knowledge readily adaptable to technological purposes. While psychologists tend not to wear labcoats these days, culturally many view psychology as the enterprise best positioned to deliver the foundational truths needed to guide such social practices as education, management strategies and policies, psychotherapy, even advertising. At the time of writing this book the American Psychological Association implicitly condones the participation of its members in ensuring scientifically warranted practices of torture. Not every psychologist took the same direction at the fork in the road, of course, nor has the discipline ever abandoned the notion that its science and practices could be closer to those Vico or Dilthey might have envisioned.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.259 | 0.152 |
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".