Bibliographic record
Abstract
Nowadays, coming to the middle of the first quarter of the21th century, the flow of life is faster than ever; social, culturateconomic and technological changes affect the approachesand the canception of the education. Frequentlyrevised education programmes introduce also a need of developingnew teaching methods and materials appropriateto themselves. Meeting the qualifications of this need "photointerpretation", as a method of values education, is one of the appropriate methods of today's constructivist educationand student-centered teaching progr amme.Photo interpretation is a measuring and evaluatingmethod both theoretically and practically appropriate to thegoals of values education.In this article it is discussed what the photo interpretationis, its advantageous and limited aspects and how to apply.Moreover, giving two sample applications, the phasesand characteristics are indicated.These two sample applications were carried out by theteachers in various branches in four different educational institutions.Before the sample application, method related informationand materials were given to the teachers. At theend of the sample applications, face to face interviews weremade with the applying teachers; then, the results and reviewswere produced.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".