Tailor-Made Training for Industrial Sector Employees
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The paper deals with the topic of the further education of employees in the industrial sector. Even though Europe today has one of its most highly qualified cohorts of young graduates entering the labour market, approximately a quarter of European Union employees have significant professional skill deficits, their professional skills are much lower compared to those needed by an average worker to be fully proficient in their job. Companies must have employees who are able to quickly adapt to an ever-changing world market. That is why they need to invest in on-going employee training and development in order to both keep their employees and be successful. Academics from Constantine the Philosopher University in Nitra have a long-term cooperation with the EATON company, a global leader in electrotechnical technologies. Within the framework of this cooperation, the university was asked by this company to assess courses which it offered to its own employees as well as employees of other companies from industrial production practices, and if appropriate to suggest an improved model of the tailor-made courses provided. The authors present a case study, the aim of which was to evaluate the effectiveness and the meeting of the objectives of the training carried out for the particular target groups of participants. They describe the methodology of the assessment carried out and the main findings resulting from it.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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