Systems breakdown in recruitment at McCune Contracting
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
Synopsis Rachel Banning was assigned a new role in HR with the responsibility to update recruitment and orientation systems to meet the rapidly growing demand for manpower at McCune Contracting, an oilfield services provider in Alberta, Canada. McCune’s industry peers were competing to attract the same skilled employees, within a relatively small talent pool. The HR team was only a few short weeks away from the upcoming peak “turnaround season” when they would be expected to recruit and deploy 500 new temporary workers for their clients’ sites. Banning knew she had to take immediate actions to fix as many of the systems issues as possible and to eventually set the team up with a more permanent solution for systems integration. Research methodology The authors had access to McCune Contracting to complete field research for this case. Relevant courses and levels The case is designed for business students at both graduate and undergraduate levels. The case can be used in operations management courses to discuss the topic of process analysis and operations strategy or in management information system courses as a comprehensive case study for use at the end of the course. The case might particularly appeal to students who have worked in human resources management areas or the service industry. Theoretical bases Theoretical underpinnings include a process view of organizational performance, internal supplier and internal customer orientation, performance improvement, information systems integration and value chain analysis.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it