Fall Issue, 2022
Bibliographic record
Abstract
The ability for workers to be authentic in the workplace benefits individuals and organizations alike. However, empirical studies examining the influences of employees' satisfaction with a supervisor and authenticity are limited, especially for employees with identities such as LGBTQIA. Therefore, this exploratory study aimed to investigate state-based versus trait-based perceived work authenticity, satisfaction with a supervisor, and the influence of sexual orientation and gender identity within one Fortune 50 company in the United States. In addition, differences in perceived authenticity and satisfaction with a supervisor were assessed by dividing participants into two groups-one as LGBTQIA and the second as cisgender and heterosexual. Quantitative data was collected with a cross-sectional online survey assessing work authenticity, satisfaction with one's supervisor, and demographic questions. The analysis and empirical tests included descriptive statistics, Pearson correlation, independent t-tests, and general linear models. Findings from this research study indicated that authenticity correlates to satisfaction with one's supervisor, and workers who identify as LGBTQIA report lower levels of authenticity, especially in self-alienation. Recommendations are provided regarding future research and improved organizational and human resource management practices for an authentic workforce or diversity and inclusion.
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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.108 | 0.009 |
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; both teacher heads agree on what is shown here.
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".