Planificación estratégica y crédito de joyas de oro en Edpyme Inversiones La Cruz, Agencia América Norte, Trujillo, 2018. (Tesis parcial)
Bibliographic record
Abstract
ABSTRACT \nThe EDYPME “Inversiones La Cruz”, does not yet have adequate strategic planning for each \nagency at the local level; that is why the present investigation has as purpose to know the \nincidence of strategic planning in the increase of gold jewelry credit in EDPYME “Inversiones \nLa Cruz”, America Norte Agency, Trujillo, 2018. We analyzed the Institution of Development \nfor Small and Microenterprise “Inversiones La Cruz” whose agency is located on America \nNorte Avenue, Trujillo, in its first quarter of this year. The population and sample is \nconstituted by 21 workers. The type of research is qualitative in nature, using a descriptive \ndesign, because reality was described and detailed as it is presented in real life, so the \ndesign of a box was used. As a technique, a survey was conducted to access the information \nand a documentary analysis was also carried out to evaluate the content collected from \n“Inversiones La Cruz” at the America Norte Agency. Concluding that 57.1 percent of workers \ndo not know that there is strategic planning and are unaware of the strategic objectives of \nthe same, which has an impact on the lack of increase in the jewelry credit portfolio during \nthe first quarter of the year. Likewise, 95 percent of workers say that if a strategic planning \nwas implemented they would gladly support it. Gold jewelry credit was evaluated in the \nEDPYME “Inversiones La Cruz”, America Norte Agency, Trujillo, 2018. Regarding \ncampaigns to increase credit assessed were implemented 6 so far this year: Campaign \nhighest value per gram, Campaign to form a team of fans, Campaign zero interest in the first \nmonth, Campaign always beautiful, Allied customer Campaign, Campaign to form your trio - \nthe third appliance worth, and finally it is observed that the quarterly portfolio in America \nNorte Agency, in January approached to the goal in 35, in the month of February it had an \napproximation of 57 and in the month of March it approached in 75. \nKeywords: Strategic Planning, Jewelry Credit.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".