Bibliographic record
Abstract
Synopsis Killing ‘em softly: terminating projects within a video game studio is a case study on human resource management (HRM) and project management in a creative setting. This disguised case is based on a real situation that was documented through individual and group interviews at a major video game studio. Several HRM and project management concepts can be discussed through this case including employee retention, planning and staffing and intracompany communication. It seeks to help students develop a multi-level, interdisciplinary and critical analysis of a common HRM situation in project-based creative sectors and invites them to devise action and communication plans to handle the termination of a project. Research methodology This disguised case is based on real events and depicts tensions as they unfolded within a Canadian major video game company. Data for this case were collected through eight individual interviews followed by two group interviews with the employees involved. Early drafts of this case were also presented to respondents in order to ensure the validity of the case. Follow-up interviews, as well as the analysis of company documents were later used to complete the case’s final edits. Relevant courses and levels This case can be used in HRM, project management and creativity management courses/modules at the undergraduate and graduate levels. It is relevant for business students in an HRM major, as well as for general administration students who plan to work in creative sectors. The case is also suitable for students in arts programs who aspire to manage creative teams or projects. It can be used as a take-home individual or group assignment, or as an in-class group activity.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".