John Goyder, The Prestige Squeeze: Occupational Prestige in Canada since 1965
Bibliographic record
Abstract
T he problem John Goyder depicts in The Prestige Squeeze has a long tradition in sociology, going back to Pareto, Sorokin, Marx, and Weber: changes in the ranking of occupations and how they come about.With such a lot of historical baggage, new hypotheses are few and far between.Goyder offers some solid and forthright ones, befitting the current state of affairs in this field: 1. education and income are highly connected to prestige, and gender, skills, occupational presentation, and characteristics of the rater influence occupational prestige rankings; 2. higher income inequality disperses prestige ratings (while individualization caps upper echelons); 3. postmodernism has a negative impact on consensus in ratings.Although the historic review contains an excellent discussion on the relationship between gender and prestige in North America, most of the merits of Goyder's research report rest on his brilliant fieldwork and data collection.For professionals in the field of data collection there are some interesting lessons to be learned from his intricate comparison of data collection methods and outcomes.For example, in terms of response rates, the undisputed top data collection method -with a remarkable 82% response -was a postal introduction letter coupled with a CATI, showing that people like to understand the goals of the research to which they are contributing.Face-to-face interviews had the lowest response rate (45.7%), and cold-call CATIs were almost as bad (56%).The hidden jewels of this book are Goyder's discussions on prestige rankings and contingencies in how they are generated in public opinion, as shown by comparisons between 1965 and 2005.Bounced to the bottom of the scale are Catholic priests (place 118 out of 124) because of recent scandals.Changes in the position of the child caregiver (with a score of 65, up 29 points from the survey in 1965) may be connected to an aging society.Why telemarketers are ranked at the bottom of the scale goes without saying -only people on social assistance are ranked below.Some of the findings make good "party talk": elementary teachers, butchers, and electricians apparently enjoyed an amazing boost in Book review/Compte rendu: the preStige Squeeze
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.026 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".