Article 1 from Series of 5 :Community Education and Development: Perspectives on Employment, Employability and Development of English-Speaking Black Minority of Quebec
Bibliographic record
Abstract
NOTE: THIS ARTICLE WAS PUBLISHED WITH THE INFORMING SCIENCE INSTITUTE. Background............................................................................................................................................................ This article serves as an overview to the conference on on “Community Education and Development: perspectives on English-Speaking Blacks and Other Minorities". It also provides a theoretical frame-work against which the reader can derive a better understanding of those papers. It allows the reader to reflect meaningfully on the optimal of the decision search rules adopted by various cultural subgroups, by comparing them to the behaviors of successful agent types in the computer simulated studies discussed in this paper. The targeted cultural sub-populations are the English-Speaking Black in Montreal. Framework and presentational approach......................................................................................................................................................... The overall research approach used is based on critical realism. We postulate that patterns in the responses of leadership in a social dynamic system may be impacted by values and uncertain events that are better explained by using a qualitative system analysis as opposed to traditional quantitative analyses based on positivist assumptions. We consider Montreal and Quebec societies diverse complex adaptive systems generating outcomes, not always predictable, in environments that vary from very hospitable to inhospitable. Findings.................................................................................................................................................................. There is a history of Black social entrepreneurship initiatives aimed at reducing the negative impact of fragmentation, gaps in communication and knowledge states, and solving the problems of integration and development posed by exclusion, racial and systemic discrimination. Who benefits.................................................................................................................................................................. This paper is of interest to social entrepreneurs, community developers and strategists; policy makers; government agencies, students and researchers
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.001 |
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".