Missing women in the boardrooms: across the board
Bibliographic record
Abstract
Purpose This paper aims to highlight the under-representation of women in leadership positions across the world. Design/methodology/approach The authors add their unbiased views in presenting the most relevant information found in literature. Findings The paper examines the representation of women in the leadership positions such as board members and/or CEOs/top executives in the corporate world across the globe to understand the new developments that may be changing the status quo. This is a review of legislative changes on bringing parity in boardrooms and its impacts in certain countries where such changes are already implemented. The changes implemented through quotas, penalties, and incentives for including women in boardrooms in certain countries in Europe, Australia, Canada, India, and Kenya show that finally the absence of women in boardrooms has been noticed. The countries are moving towards legal compliance; however, there is still a dearth of women CEOs around the world. Practical implications The paper points toward the fact that the interventions that have happened are late and have failed capable women who could have reached their full professional potential in the western world. Also, taking a cue, the rest of the world can impose sufficient and timely legislative change to leapfrog to a gender equal society at every level, including at the top. Originality/value The paper compiles the most significant facts and figures and presents them in a very concise manner for any busy executive or researcher thus saving hours of reading time.
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.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".