PRODUCTION UNIT ANALYSIS OF INFLUENCE ON REAL WAGES AND \nLABOR ABSORPTION IN INDUSTRIAL OF TAPIS \nIn Bandar Lampung
Bibliographic record
Abstract
Abstract \n \nThe basic problem is to maximize economic development in a productive job \ncreation is sustainable. In an effort to place of employment provision as a starting \npoint in attempting humans Indonesia became the main force of development. In \nIndonesia, the rate of population growth is not matched with the equitable \ndistribution and lack of labor market. \nProblem of expansion of employment opportunities is one of the main problems \nof today, but basically there is a way to expand employment opportunity, namely \nthrough the development of labor-intensive industries (Labor Intensive) which \nabsorbs relatively more labor in their production process. Relation to the \neconomy, small industries, especially industrial of Tapis can improve the \neconomy, especially developing countries like Indonesia, which has a workforce \nthat quite a lot. \nThis study aims to determine the effect of variable units of production and real \nwages to labor absorption in the industrial of Tapis in Bandar Lampung period \n2004.1 - 2008.4. The analytical method used is ordinary least square, followed by \nhypothesis testing and simultaneous partially through t test and f. The results in \nthe period 2004 - 2008 by Data quarter we concluded that, based on the \ncalculations and discussion, conclusions that can be given by the authors is that \nthe results of calculations and statistical tests as a whole (F test) at the level of \nconfidence of 95 percent, indicating that the value of R ² = 0.763820 which means \nthat the variable unit of production and real wages have a real impact for 76.3820 \npercent of industrial labor absorption of Tapis in Bandar Lampung. While the \nremaining 23.618 percent is influenced by other factors beyond the model of this \nresearch. Meanwhile, according to t test independent variables that turned out \nproduction units have positive and real wage variables negatively affect the \nemployment screening industry in Bandar Lampung. In calculating the \nindependent variable is the elasticity of production units and real wages can be \nconcluded: \na. Variable elasticity coefficient calculation unit of production equal to \n0.023646217 show flexibility towards the development of production units of \nlabor absorption. This means an increase of one percent of the production units \nwill result in increased employment of .023646217 per cent, assuming the other \nvariables fixed (ceteris paribus). \nb. Variable coefficients calculation real wage elasticity of - 0.035582521 showed \nstagnanasi real wages of labor, meaning that real wages decline by one percent \nwould reduce employment of - 0.035582521 per cent, assuming other variables \nfixed (ceteris paribus) .
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".