Hiring Your Next Partner
Bibliographic record
Abstract
Hiring a new partner into an orthopaedic department or group can be a daunting task. A recent American Orthopedic Association symposium sought to address three major aspects of hiring that affect orthopaedic leaders: (1) when to hire-the chairperson's role; (2) generational issues that affect hiring; and (3) the development of an initial compensation package.How does the chairperson recruit new physicians? Hiring a new partner into the academic setting requires a good deal of foresight. There must be an established game plan. Advertising and interviews need to be orchestrated. Chairpersons can find information about candidates from many unique sources. Fit within the department and community is important and must be cultivated. Spouses and families need special attention. Research candidates have individual needs. Perhaps the most important aspect of recruitment is the development of a realistic business plan. This paper provides an overview of factors to consider in managing a new hire.Generational issues are intriguing. Should they affect our hiring practices? It seems clear to established physicians that the new generation of graduates is different from their predecessors. Is this really true? Most everyone is familiar with the terms "Silent Generation," "Baby Boomers," "Generation X," and "Generation Y." Is there anything to be gained by categorizing an applicant? Is it important to hire a replica of one's self? This paper provides a thoughtful overview of generational issues as they apply to hiring new partners.Most department chairpersons are not trained as negotiators. Some preparation and experience are helpful in guiding the process of making an initial offer to a candidate. It is not all about pay. The package includes the guarantee period, expectations for the new hire, mentorship, and resources. How much should new orthopaedic academic hires be paid? Recent benchmark data from the Academic Orthopaedic Consortium suggest a mean income of $282,667 for physicians who have just finished a fellowship. New hires are concerned about call frequency and available time free from work. How much work should be expected from an academic surgeon? Recent survey data from the American Orthopaedic Consortium suggest a mean of 9200 relative value units per year. This article offers some guidelines for the chairperson who needs to formulate an initial offer for a new hire.There is a lot involved in hiring a new partner, as times are changing. This paper offers considerable food for thought about hiring.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.316 | 0.178 |
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".