Bibliographic record
Abstract
In the Preface to his classic study, Education as a Profession, Myron Lieberman charged that "one of the major obstacles to the professionalization of education (was) the widespread failure of the public to understand the conditions necessary for it." Nearly two decades have passed since the publication of Education as a Profession and no doubt public ignorance of the conditions necessary for the professionalization of education is as widespread as it ever was. But what is more discouraging is the continuing evidence of the widespread failure of educators, themselves, to understand the conditions necessary for their professionalization. Symptomatic of this failure is the ubiquitous and indiscriminate usage of the term 'professional' by educators. This term is used and misused to describe (and prescribe) all manner of diverse behaviour (e.g., "Tardiness is unprofessional, etc.".) Indeed, it is progressively less clear whether the term 'professional' is a noun or merely an adjective ( or worse, a slogan) used to characterize certain things considered desirable at the moment.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.028 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.017 | 0.033 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".