Attitudes toward Affirmative Action Programs: A Q Methodological Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examined the structure and content of attitudes toward affirmative action programs, including preferential hiring based on gender or minority group status. Ninety-seven individuals recruited from the community (51 women, 43 men, 3 of unspecified gender), were presented with 70 statements obtained in a telephone survey of attitudes toward affirmative action programs. They sorted the statements on an 11-point scale ranging from -5 (least like my point of view) to +5 (most like my point of view). The Q sorts were factor analyzed using principal components analysis with varimax rotation. Three interpretable factors emerged. Factor 1 was defined by 15 women and 28 men. The group expressed strong negative reactions to affirmative action programs, focusing mainly on qualifications and merit of candidates. Factor 2 was defined by 22 women and 6 men. In contrast to the first group, participants on this factor were in favor of affirmative action programs, a position that appeared to be based on recognition of inequality in the work place and the need for change. Finally, Factor 3 was defined by 7 women and 6 men, whose attitudes seemed to be based primarily on the denial of disadvantage. Despite the fact that affirmative action policies have been in effect for as long as 30 years, only a relatively small proportion of respondents appeared to understand the need for and goals of these policies. Results of this research provide new insights and a basis for work to change misconceptions about affirmative action. Comparisons between a single-item attitude measure and the 3 perspectives represented in this study help to illustrate the usefulness of Q methodology in subjective studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it