Socially Constructing Discrimination Against Women in the Workplace
Bibliographic record
Abstract
Since the mid-1950s, women have achieved academic success and slowly entered male\n dominated fields of work. However women continue to face discrimination in the workplace\n regardless of the equality rights guaranteed in the Canadian Charter of Rights and Freedoms,\n in section 15(1). Previous biological research on gender differences show that areas relevant\n to work such as problem-solving abilities and motivation to manage, men and women appear\n to be more alike than different. Thus, this essay argues that both men and women are equally\n capable of working in similar positions and discrimination is a social construct built upon gender\n stereotypes and social expectations, which as a result affect women negatively in the workplace. To support this claim, this paper aims to address how discrimination in the workplace is performed through gender stereotypes, how gender stereotypes are socially constructed, and how these gender stereotypes negatively affect women in work-related situations.
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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 | 0.019 | 0.018 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".