Which Future Skills Are Critical to Success Today and in the Future? Quantitative and Qualitative Study Based on a Survey of Representatives of German Industrial Firms and Associations in Manufacturing
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
Purpose: The study aims to provide company managers with a basis for considering the need for company-specific future skills and deriving suitable and sustainable qualification measures from this in good time. Design/methodology/approach: Based on an online survey of works council committees and HR departments, the question is to be answered as to which competencies will be imperatively needed in the future in order to be able to meet future tasks and requirements in the professional world.  Findings and Originality: The study aims to identify current needs and anticipate skills gaps. This should enable companies today to identify and build up the necessary skills of tomorrow. The study can serve as an impetus for a strategic orientation in the human resources policy of companies. In this way, it makes a contribution to ensuring competitiveness in the long term and placing the human factor at the center.
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 | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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