Helpful Today, But Not Tomorrow? Feeling Grateful as a Predictor of Daily Organizational Citizenship Behaviors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This research extends the existing theoretical understanding of what predicts organizational citizenship behavior (OCB). Using experience sampling techniques, we examine the within‐person relation between OCB and a novel, theoretically relevant predictor: state gratitude. Using 4 independent samples with a total of 210 working adults and 173 undergraduate students, we developed a reliable and valid measure of state gratitude. Drawing upon the moral affect model of gratitude and affective events theory, we conducted 2 experience sampling studies with data collected from 67 (Study 2) and 104 (Study 3) working adults to test the effects of state gratitude on OCB, beyond the effects of several relevant constructs (i.e., state positive affect, dispositional gratitude, and social exchange). Our results advance OCB research and explanations of OCB by modeling OCB as a dynamic, time‐variant construct and by demonstrating that feelings of gratitude, a discrete positive emotion, can be an effective predictor of OCB.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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 it