Bibliographic record
Abstract
This project is designed to understand the different generations coexisting in the workplace and create recommendations for corporate leadership on most effectively managing and developing leadership competencies in the younger generation. This investigation, examined through secondary sources and interviews with 20-35 year-olds, provides insight on the tools upcoming leaders need in order to build on current corporate success. Current research from psychology and business journals, and publications released by consulting companies and other sources was consolidated to evaluate the status of the workforce given the recent generational spread. Interviews were conducted with twelve employees and consultants from various industries in Calgary to understand their workplace values, definition of effective leadership, career aspirations, and views on their needs from current employers. Gen Yer’s and Traditionalists want to learn from one another in order to combine skills and strengths. This learning should take the form of both structured and informal mentorship as well as 360-degree feedback. The incoming generation wants a company to invest in them, which many companies are reluctant towards because they accurately believe Gen Xer’s and Yer’s have less longevity. The paradox lies in the reality that this generation is drawn to an environment in which their capacity for learning and opportunities are extensive. They are eager to build their careers with a company that helps them access a range of experiences, understand the ‘big picture’, and fosters challenging and meaningful work. Younger workers expect a culture of transparency, teams over hierarchies, respect for personal life, and trust.
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.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".