Bibliographic record
Abstract
The purposes of this presentation are to analyze the subscription trends ubiquitous in the Journal of North-East Asian cultures published from the Association of North-East Asian Cultures and seek for the future directions of the journal. The Associations of North-East Asian Cultures were established in July, 1998 and has published articles on quarter’s basis (May, June, September, and November). Focusing on Korea, China, Japan, and Russian cultures, the journal aims at establishing East Asian Cultural Community rooted from the chapters from diverse academic disciplines’ discussions and explorations. Throughout the analysis of the articles published with the journal for the sake of proposing the future directions, it is no wonder to say that the analysis should entail the types of the journal published and multiple perspectives voiced from one nation to the other. Journal of North-East Asian cultures deals with complex learning fields, and thorough the active access toward the interdisciplinary fields, the journal tries to shatter commonly held academic biases in the hoping that this will eventually extend the journal’s academic specialties. The Association of North-East Asian Cultures explores issues relevant to Humanities and Social Sciences in the East Asian region, and the categories of the thesis consist of six domains. The presenter analyzed the articles published from volume 1 of 2004 to volume 19 of 2016 on the basis of the author’s distribution in terms of nationality and will report the present condition of international conferences held abroad up to now. The presenter will critically address the relationships between the dominant themes omnipresent from the previous studies and propose an optimal, future directions of the Journal of North-East Asian cultures.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.100 | 0.065 |
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".