A Written Child Corpus with Editing History Tags
Bibliographic record
Abstract
自然言語処理や言語学においてコーパスは重要な役割を果たすが，従来のコーパスは大人の文章を集めたコーパスが中心であり，子供の文章を集めたコーパスは非常に少ない．その理由として，子供のコーパスに特有の様々な難しさが挙げられる．そこで，本論文では，子供のコーパスを構築する際に生じる難しさを整理，分類し，効率良く子供のコーパスを構築する方法を提案する．また，提案方法で実際に構築した「こどもコーパス」についても述べる．提案方法により，81人分（39,269形態素）のコーパスを構築することができ，提案方法の有効性を確認した．この規模は，公開されている日本語書き言葉子供コーパスとしては最大規模である．また，規模に加えて，「こどもコーパス」は作文履歴がトレース可能であるという特徴も有する．
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.047 | 0.010 |
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".