Bibliographic record
Abstract
This chapter undertakes a socio-cultural critique of the ‘instrumental instruction’ workplace e-learning scenario. This scenario includes workplace e-leaning interventions that are designed to culturally decompose the workforce through abilities, beliefs, and behaviours. The goal is to use workplace e-learning to make workers more able to cope with periodic and on-going ICT innovation and business process change within organizations. An exploratory case study brings together the elements of process, technology, and culture. This provides a more holistic understanding of the experiences of the workforce and management when it comes to continuous ICT innovation, business process change, and a culture of instrumentalism. All this bears significant socio-cultural impacts on the workforce that come about through the workplace e-learning scenario of instrumental instruction. Socio-cultural insensitivity from workplace e-learning, in this scenario, comes from the basic, unquestioned assumption that workers are essentially socially flawed and culturally inferior; accountable for overcoming their socio-cultural flaws and inferiorities; and, need to be decomposed by workplace e-learning, through abilities, beliefs and behaviours, to meet the expectations of the infallible and commodified workplace. Workplace e-learning is now increasingly relied upon by organizations to provide the instrumental instruction that brings about cultural change in the workforce in terms of cultural decomposition of the workforce. In the wider marketplace, technological innovation in the ICT sector, accompanied by business process change in organizations, continues to culturally influence workplace e-learning industry trends and strategies. Workplace e-learning industry trends and strategies also culturally shape workplace e-learning. Instrumental instruction from workplace e-learning thus signifies the instrumentalization of instruction for workers, by workplace e-learning through their abilities, beliefs and behaviours, to culturally decompose the workforce for a knowledge- based workplace.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".