Bibliographic record
Abstract
연구목적: 본 연구는 Richard D. Lane이 인지발달이론에 기초하여 감정의 경험을 평가하기 위해 개발한 Levels of Emotional Awareness Scale(LEAS)를 번역하고 그 타당도와 신뢰도를 검증하여 한국판 감정자각 수준 척도(LEAS-K)를 개발하고자 하는데 목적이 있다. 방 법: LEAS를 일차번역과 역번역의 과정을 거쳐 가능한 원문에 가깝게 번역을 한 후 문화적 차이를 고려하여 수정한 것을 최종 연구 자료로 사용하였다. 경북대학교 의예과와 의학과에 재학 중인 학생 476명(남자 322명, 여자 154명)을 대상으로 검사를 시행하여 신뢰도를 알아보았으며 타당도를 검사하기 위해 한국판 감정표현불능증 척도(TAS-20K), 개방성 척도(Openness to Experience Inventory), 사회 바람직성 척도(Marlowe-Crowne Scale), 외현 불안 척도(Bendig short form of the Taylor Manifest Anxiety Scale), 정서 표현성 척도(Emotional Expressivity Scale)를 같이 시행하였다. 결 과: LEAS-K의 내적 일치도(internal consistency)는 Cronbach's alpha 계수 0.81이었으며 검사자간 신뢰도는 0.99였다. LEAS-K와 TAS-20K는 부적 상관관계(r=-0.10), 개방성 척도, 사회 바람직성 척도와는 정적 상관관계(r=0.10)가 있었으며 통계적으로 모두 유의하였다. 외현 불안 척도, 정서 표현성 척도와는 통계적으로 유의한 상관관계가 없었다. 결 론: LEAS-K는 신뢰도와 타당도가 만족할 만한 수준임을 알 수 있었고 감정을 경험하는데 있어서 감정의 강도보다는 감정 경험의 구조(structure)나 복합성(complexity)을 측정하는 척도임을 시사하였다. 【Objectives: The purpose of this study was to develop a Korean version of the Levels of Emotional Awareness Scale(LEAS-K) and to examine its validity and reliability. Methods: LEAS-K was developed from translating original LEAS into Korean. The subjects were 476 Korean medical students(322 males and 154 females). The internal consistency was evaluated with the Cronbach's alpha coefficients and 40 protocols were independently scored by two raters to confirm interrater reliability. Additionally, a Korean version of 20-item Toronto Alexithymia Scale(TAS-20K), Korean versions of the Openness to Experience Inventory(OE), the Marlowe-Crowne Scale (MCS), the Bendig short form of the Taylor Manifest Anxiety Scale(TMAS) and the Emotional Expressivity Scale(EES) were rated to evaluate concurrent validity. Results: The internal consistency measured by Cronbach's alpha was 0.81 and interrater reliability was high{r(40)=0.99}. Correlation coefficients for concurrent validity were nonsignificant with TMAS and EES. LEAS-K correlated significantly with TAS-20K{r(476)=-0.10, p】
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.048 | 0.023 |
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".