A Study on Developing the Business Index of Electrical Construction Business
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Bibliographic record
Abstract
현재 전기공사업계는 경기분석 관련한 정보자료가 부재하여, 건설업계 경기전망을 활용하고 있다. 전기공사업은 건설업과 다른 고유한 특성이 있어 독자적인 경기지수 개발이 필요한 실정이다. 전기공사업 경기지수는 전기공사업 경기종합지수(ECI)와 전기공사업 경기실사지수(EBSI)로 구성된다. 전기공사업 경기종합지수(ECI)는 전기공사업 경기에 민감한 영향을 주는 개별 경제지표들의 움직임을 종합 지수(index)화하여, 경기동향을 파악하고 향후 경기를 예측하는데 활용된다. 전기공사업 기업실사지수(EBSI)는 기업의 실적과 계획, 경기동향 등에 대한 전기공사업체 대표들의 의견을 조사 지수화하여 미래의 경기를 판단 예측하는 데 활용된다. 본 연구는 '14년 2/4분기를 대상으로 실증 분석하였다. 전기공사업 경기종합지수의 경우 경기선행지수는 전분기 대비 0.4% 하락, 경기동행지수는 지속적인 하락국면에 있는 것으로 파악되었다. 그리고 전기공사업 기업경기실사지수(EBSI)는 전분기비 11.7p 하락한 83.5을 전망되었다. 따라서 '14년 2/4분기 전기공사업 경기상황은 좋지 못한 것으로 예상되었다. 전기공사업 경기지수는 전기공사업의 경기동향을 파악하고 장래의 경기를 예측함으로써, 전기공사업체가 경영전략을 수립하고 경기변화의 대응책을 마련하는데 기여할 것으로 사료된다. Electrical Construction industry uses Construction industry's statistical data for business outlook. Because there are not electrical construction business view's statistical data. It has own unique characteristic which is different from construction industry. So it must have a electrical construction Business Index. This study was focused on developing the business index of electrical construction business. Electrical construction business index consists of electrical construction composite Index(ECI) and the electrical construction business survey index(EBSI). This study experimentally analyzes the business views of electrical construction industry in 2/4 quarter of 2014. The leading Index of ECI indicates -0.4% compared with 1/4 quarter of 2014, coincidence index also shows that electrical construction industry's business cycle is in an economic downturn. EBSI is 83.5 in 2/4 quarter of 2014, down from 95.2 in 1/4 quarter of 2014. It means that electrical construction company has a pessimistic prediction. As a result we know that the Business Index of Electrical Construction Business shows similar results. It is expected to make contribution for electrical contractors to establish management strategies and prepare responses to economic changes by providing information about economic trends of electrical construction business and forecasting future economy.
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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 | 0.000 | 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 | 0.000 |
| 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 it