Bibliographic record
Abstract
Purpose The purpose of this study is to examine the existence of the glass ceiling in Texas. Design/methodology/approach Data on publicly traded corporations registered in the state of Texas was used to examine the existence of the glass ceiling effect in Texas. The data for this study were gathered from ReferenceUSA, which is a subscription database that contains information on more than 12 million US businesses and one million Canadian businesses. Findings The study found the existence of the glass ceiling based on the analysis of the sample. Of the 257 corporations in the sample, there were only two that had women chief executive officers (0.78 percent). Research limitations/implications The dataset used was not a comprehensive list of corporations registered in Texas. Practical implications Given the increase in ethnic and gender diversity at the work place, it is critical that women feel assured of an equal opportunity to reach top‐management positions. Originality/value Although there have been other studies in the field, none have focused on Texas which is the second largest US state in area (after Alaska) and in population (after California). It is hoped that the results add value to the existing literature.
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 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 | 0.012 | 0.001 |
| 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 | 0.002 |
| 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 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".