Balance between Merit and Equity in Academic Hiring Decisions: Judgemental Content Analysis Applied to the Phraseology of Australian Tenure-stream Advertisements in Comparison with Canadian Advertisements
Bibliographic record
Abstract
The wording of university academic job advertisements can reflect a commitment to equity (affirmative action) as opposed to academic merit in hiring decisions. The method of judgemental content analysis was applied by having three judges rate 810 Australian tenure-stream advertisements on seven-point magnitude scales of equity and merit. The influence of time (Years: 1970-1973; 1984-1987; 2000-2003), institution (major research universities (the self-designated Group of Eight - Go8); colleges of advanced education and institutes of technology; regional and distance education), as well as academic discipline (physical sciences and technology; social sciences; humanities) on ratings were also examined. Inter-rater reliabilities were high (= 0.92), and the 'equivalence hypothesis' (that merit and equity are the same) was not supported. Merit and equity criteria increased over time and were influenced by institution type and academic discipline, although in different ways. While some effects could be viewed as being due to rational policy decisions, other significant effects suggested influences that are more difficult to explain. University administrators need to be sensitive to the balance between merit and equity when formulating hiring policies.
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How this classification was reachedexpand
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".