Bibliographic record
Abstract
Abstract Previous research shows that females use more exclamation marks than males, often to establish rapport. The purpose of the present studies was to test whether people associate texters’ use of exclamation marks with friendliness and femaleness. If this association is due to normative expectations, we hypothesized that females would appear less friendly if they did not use an exclamation mark in texting. In Study 1, participants rated a texter using an exclamation mark to be highly female and highly friendly. The gender results disappeared when friendliness was controlled for. In Study 2, we tested whether friendliness ratings decreased if texters violated gender-associated punctuation. Participants rated a texter with a gendered name on friendliness. Regardless of gender, participants inferred greater friendliness to texters using an exclamation mark. That is, there was no evidence of a cost for violating this gender expectation. We conclude that people predict that a texter using an exclamation mark is likely to be female, but do not penalize females for not using an exclamation mark.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".