Wiring the Nation! Including First Nations? Aboriginal Canadians and Federal e-Government Initiatives
Bibliographic record
Abstract
Governments are turning to new information and communication technologies (ICTs) to enhance service delivery and improve citizen-state relations. E-government initiatives are focused on renewing administrative structures and processes, and on providing government information and services online. Emerging e-governance initiatives include the use of ICTs, particularly the World Wide Web, to create new patterns of engagement between policy communities and policy-makers. This essay identifies and assesses the Canadian federal government's efforts to ensure that the needs and interests of Canada's indigenous peoples are included in the wired world of government policy initiatives. The essay reveals that beyond the technological infrastructure needs of the First Nations peoples and their communities, federal policy initiatives must address and respond to the non-technical policy issues — from the cultural considerations to the privacy concerns that may be unique to the needs and interests of diverse indigenous communities in Canada — that may constrain the realization of ICTs to support Native peoples' socio-political and economic development objectives.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.045 | 0.017 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".