The Future Lives of Sociology Graduates
Bibliographic record
Abstract
After earning a bachelor's degree, the fate of sociology undergraduates is mysterious. We know little about how many Canadians have sociology degrees and even less about what they do after graduation. Using a variety of data sources from Statistics Canada, we paint a historical portrait of the discipline by charting how many people, and who, become sociologists. We also examine where they are employed, how much they earn, and how satisfied they are with their degrees. Our findings show that sociology graduates are competitive with other fields of study on both wages and employment, but are less satisfied with their degrees. We stress how the discipline would be wise to pay more attention to our graduates and their opportunities. Nous en savons peu sur l'avenir et le nombre de Canadiens ayant des diplômes de sociologie et encore moins ce qu'ils font après la graduation. Grâce à des données de Statistiques Canada, nous dressons un portrait historique de la discipline en montrant combien de personnes, et quel genre de personnes, deviennent sociologues. Nous examinons aussi où ils travaillent, combien ils gagnent et leur niveau de satisfaction par rapport à leurs diplômes. Nos résultats démontrent que les gradués en sociologie sont compétitifs par rapport aux autres champs d’étude en termes de salaire et de taux d'emploi, mais qu'ils sont moins satisfaits de leurs diplômes. Nous notons que la discipline aurait intérêt à porter plus d'attention sur les gradués et leurs opportunités.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".