Bibliographic record
Abstract
What is the state of digital adoption by businesses? Are businesses able to leverage and keep up with the rapid pace of technological change? What policies are needed to ensure robust adoption by start-ups and small businesses? This panel will take stock of business adoption in the enterprise and small business sectors of Canada, and explore the challenges and opportunities to digital technologies. A new body of Canadian research has shown that the majority of businesses are online and using a range of digital tools, from social media to e-commerce to mobile applications. A report by the Canadian Federation of Independent Business that polled over 2000 small and medium sized enterprises concludes that businesses of all sizes and from all sectors are adopting various digital technologies in their operations. Arriving at a similar conclusion a report by Start-up Canada, a trade association representing the Canadian start-up community determined that digital networks have vastly expanded potential market opportunities for small businesses, enabling them to reach customers world-wide. Yet, the research also highlight clear challenges and persistent divides in digital adoption among businesses. The reports broadly agreed that the complexity and time required to adopt digital tools is a significant challenge. The report from Start-up Canada highlighted the pressure of digital onboarding, technology implementation, and maintenance as a significant upfront investment in time and cost for small business owners. An OECD report suggests that training is a barrier to adopting digital technologies in Canada and other G20 nations. Data from the Canadian Chamber’s survey revealed that only 37% of businesses invest in digital skills literacy, 50% invest in software training and only 31% invest in cybersecurity training. Moreover, survey data show that specific groups are particularly unequipped to leverage advanced digital tools. Women entrepreneurs are 20 per cent less likely to leverage digital technologies when operating their business than men. At the same time, digital adoption rates are two times higher amongst immigrant small business owners (SBO) than born-Canadians. Immigrant SBOs are also more likely to both leverage digital technologies in their companies and invest in digital skills building. These findings raise questions on the trends and barriers to online adoption. What are the hurdles inhibiting participation beyond the cost of access? How can we formulate policy that sparks adoption? With the aim of widening and deepening the TPRC community’s knowledge of adoption issues, this panel will frame the challenge and ignite a data-driven, candid conversation using Canada as a case-study. The TPRC community will grapple with the big and broad question on how to ensure that the internet remains a meaningful and transformative technology the digital economy. The panel will be composed of the following voices. Panelist #1 will discuss a Canadian research study that provides insights on internet usage in the small business and start-up scene. Panelist #2 will provide a deeper dive into the challenges felt by enterprise-size businesses. Panelist #3 will consider the trends internationally, including but not necessarily limited to North America.
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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 | 0.016 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.023 | 0.044 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".