Psychometric Assessment and Refinement of the Family Issues Scale of the Human Dimensions of Operations (HDO) Project
Bibliographic record
Abstract
The present report summarizes psychometric analyses and recommendations for item refinement of the Family Issues scale a measure included a predeployment survey of operational stress among Canadian Forces personnel. Inspection of the items comprising the Family Issues scale revealed two distinct sections. The first section included 14 items that assessed respondents' family concerns in anticipation of their upcoming deployment with a Liken scale (i.e., 1 - strongly disagree to 5 - strongly agree). The second section assessed respondents' knowledge of the availability of family oriented support services. As the two sections of the Family Issues Scale assess distinct dimensions, and because these sections used different scaling techniques, each section was treated as a separate scale: Family Attitudes and Perceived Support. Exploratory factor analyses of the items comprising the Family Attitudes scale yielded two separate factors: Family Concerns and Positive Attitudes. Subsequent reliability analyses of these two factors indicated that the Family Concerns factor had a robust alpha value of .81. Reliability analyses of the items within the Positive Attitudes factor were disappointing, however, resulting in a very low Cronbach's alpha of .49. The items within the Positive Attitudes factor do not appear to tap a single underlying dimension, and the inclusion of these items in further studies is not warranted. A monomethod-multimeasure analysis was also conducted to determine the relative validity of the Family Concerns and the Family Attitudes scale. Two versions of the Family Attitudes scale were used in this analysis: (1) a version that included the entire 14 items, and (2) a revised 11-item version, constructed to preserve as many of the original Family Attitudes scale. This analysis revealed patterns of correlations that substantiated most hypotheses.
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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 | 0.034 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".