Running head: ATTITUDES TOWARDS MALE SEXUAL ASSAULT 1 Male County Correctional Facility Inmates ‟ Attitudes Towards Male Sexual Assault and Sexual Assault Services
Bibliographic record
Abstract
First, I would like to acknowledge my father, Jesus Christ, for loving me, being my strength, my direction and my backbone. I would like to thank my family for being my backbone and supporting me in all of my endeavors. To my grandmother, I would like to thank you for always babysitting my children, so that I can accomplish my dream of obtaining my Master‟s Degree. Grandma, thank you for praying for me and teaching me how to pray. Mom, thank you for the values and beliefs you instilled in me, and thank you for never allowing me give up and always believing in me when teachers, and society wrote me off as a disabled child who would not likely graduate from high school. You are always there for me especially when I became a young mother, and I cannot ask for more. Nayilah, my dearest daughter, I cannot articulate how much I love you, and I hope through me you will learn that as an African American female you can do anything as long as you stay committed and not be afraid to walk alone. Rodney Jr., my sweat son, once again I cannot articulate how much I love you. You always put a smile on my face when I am sad. I hope through me you will learn the value of love, hard work and
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".