Bibliographic record
Abstract
At the macro-level, this study investigated the role of education in the adaptation process of adult immigrants. Migration was defined as a developmental event, adaptation was described as the process by which that event is resolved, and learning and education were differentiated using Alleyne and Verner's typology of sources of information. At the micro-level, these concepts were applied to the case of Israeli immigrants to Vancouver, B.C. Four general research questions were posed with respect to the kinds of tasks emerging during adaptation to life in a new society, the relationship of a variety of socio-demographic and other factors to the perceived difficulty of tasks and the use of adult education sources of information in resolving tasks of adaptation. An analytical survey, employing an interview schedule, a magnitude estimation scaling device to measure relative difficulty of tasks and a series of other measures of factors thought to be related to difficulty, was conducted early in 1977 with seventy-two respondents. Analysis included computation of geometric mean difficulty scores, calculation of univariate frequency distribution of socio-demographic variables and of scores of other factors as well as means and correlation co-efficients. Step-wise regression analysis utilized difficulty scores as dependent variable and ten socio-demographic measures as independent variables in an attempt to ascertain the predictive ability of the socio-demographic variables with respect to difficulty. Results of the data analysis identified the most difficult task, finding a satisfying, career-oriented job, indicated that the majority of other tasks of adaptation were being resolved using non-educational sources of information, and that the construct "difficulty" might better be renamed "extent of cultural innovation required" and further investigation of this factor be conducted. Implications were drawn regarding the use of magnitude estimation to assess educational needs of adult immigrants, and the development of policy and programs which meet the needs and aims of both Canadian society and the immigrant learner.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 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".