Bibliographic record
Abstract
In reply to some comments on the future development of psychology (Buss, 1975), Abrahams et al. (1975) have pointed out some additional complexities which I failed to consider in my article.Their concerns fell into two categories: the job market and the question of dialectical development within a discipline.In regard to the first issue, a decline in the numbers of new PhDs will tend to ensure that those who are able to enter the profession will be, in the main, the most qualified and motivated.Such a raising of stan dards, brought about by recent socioeconomic conditions, would seem to be beneficial to the discipline to the extent that there is increased competition to excel at the lower ranks.While, in general, I agree with this interpretation, such a selection may still result in an overly conservative and inflexible discipline in which older academicians outnumber new academicians.What would be the most desirable age structure of an academic discipline?As pointed out by Riegel (1975), academicians at various points in their career development tend to perform different functions in advancing their discipline.All of these functions are necessary and important at any given point in time, the implication being that the full age strata constantly need to be well represented within the discipline.Are current socioeco nomic conditions adversely affecting the replacement of junior academicians at a level necessary for adequate representation?I think so, but this is purely a subjective judgement on my part.With respect to the question of dialectics and development, Abrahams et al. (1975) appropriately take me to task for failing to mention two important dialectical relationships in a d d itio n to th e academ ician-discipline dialectics.T hey e la b o ra te o n th e academ ician-
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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 | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.037 | 0.054 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".