The influence of gender of the board of directors on the financial performance of Australian public companies
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
The aim of this research is to investigate the influence of gender of the board of directors on the financial performance of Australian publicly listed companies, in order to establish if there is a relationship between the number and percentage of women on the board and firm’s financial performance. The starting point for this study is to understand the board of directors and their responsibilities, then to investigate some of the previous studies in this field and their findings. Using the resource based theory the hypothesis that firms employing greater percentage of women on their boards will experience relatively better financial performance is developed. <br><br>The findings identify that the number and percentage of women on board have a positive relationship with firm’s financial performance in three of four of the financial measures that have been tested (net profit after tax, increase on total equity, capital increase and market value).<br><br>The study also indicates that the number and percentage of women on Australian boards remains low compared with other countries like US, UK and Canada. The study considers some of the reasons behind the low representation on women on Australian boards and suggests ways for women and companies to improve this percentage.<br>
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it