Contemporary Cultural Resource Management in Canada: Labor Market Dynamics and Challenges
Bibliographic record
Abstract
Abstract Cultural resource management (CRM) archaeology is a multimillion-dollar industry in Canada and the lead employer for archaeology graduates. Yet, the growth of and the challenges facing the Canadian CRM industry remain poorly documented. We therefore designed and distributed a job satisfaction and labor market survey to Canadian CRM practitioners with the goal of understanding how industry professionals feel about their positions and the health of the industry as well as what they believe are the most pressing challenges facing the Canadian CRM industry. These data indicate that the sector has grown faster than the supply of labor, that owner-operators are faced with difficult challenges related to the staffing required for the scale and volume of work, and that employees in the CRM sector are experiencing frustration with working conditions, compensation, and the preparation that postsecondary training offers. In this article, we attempt to determine the size of the Canadian CRM industry and highlight the challenges faced within the industry that must be addressed for CRM in Canada to attract and retain professional archaeologists.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".