Impact of Locus of Control Expectancy on Level of Well-Being
Bibliographic record
Abstract
This paper investigates the impact of locus of control, a psychological social learning theory that is rigorously researched for its implications on leadership qualities, on the level of happiness of an individual. The primary research strategy employed was the survey strategy. Participants were asked to fill in a questionnaire that was designed to test, amongst other variables, their locus of control and level of happiness. The Spearman Rank Correlation hypothesis test was used to test the data for significance and strength of the relationship. As a secondary research approach, self-reflection documents written by research participants, on the topic of locus of control, were used to add personal expression to the discussion of the quantitative results. While academic literature vastly supports the view that leadership qualities are predominantly present in those with an internal locus of control, our research results conclude that a maximum level of happiness is achieved by individuals with a balanced locus of control expectancy – a mix of internal and external locus of control, alternatively known as ‘bi-local expectancy’.
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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 | 0.011 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".