The Effects of Social Environment on Pronouns as a Measure of Self-Awareness
Bibliographic record
Abstract
By analyzing the types of words used in people’s writing, we can make inferences about the different psychological states individuals may be in. According to previous research, the types of pronouns people express in their language can give information about their focus of attention. Greater use of first person singular pronouns is indicative of higher levels of self-awareness. People's focus of attention can be shifted towards the self by placing a mirror in front of them, or shifted to others by having other people present. This study manipulated levels of self-awareness in individuals, and then measured the pronoun usage in their writing using Linguistic Inquiry and Word Count (LIWC2007). The results showed that the mirror condition displayed a significantly higher frequency of first person pronouns compared to the group condition. These results indicate that an individual setting with a mirror increases self-awareness, and that a group setting with no mirror reduces self-awareness. Researching self-awareness is important because it is a basic trait in humans, and a lack of, or excessive levels of self-awareness may indicate psychological problems, thus it can be applied to the study of mental disorders such as depression and mania.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".