Secondhand Is First-Rate: Don't Be Deterred by the Stigma of Buying Used. Refurbished Computers Can Offer Better Value and Performance Than New Units, While Lessening IT's Environmental Footprint
Bibliographic record
Abstract
CONSIDER THIS: BEFORE YOU PRESS the power button a brand-new computer for the first time, it has already used almost i percent of the energy it will consume over its lifetime. Eric Williams, an assistant professor at the Center for Earth Systems Engineering Management at Arizona State University, has been researching life cycle assessments of IT machines since 2000. Life cycle assessments measure the total environmental impact of a product or service, from the resources used in its manufacturing to the energy consumed during its intended operation, all the way through to the method of its disposal. you do a life cycle assessment of an automobile, Williams says, what you'll find is that 95 percent of the energy consumed will be from driving it. other 5 percent will be in the manufacturing--the steel, the plastic, the different parts that need to be made assembled. So gas mileage is going to be a huge factor in how environmentally friendly it is. Computers operate differently, Williams explains. require a far more intensive process in the manufacturing stage. Part of this is due to the high-tech components scrupulous environmental conditions required to build one. Anything that gets near semiconductors microprocessor chips has to be immaculate. It takes energy, chemicals, processing to make the chemicals, gasses, water that touch the unit that pure, Williams says, and to keep them that pure. [ILLUSTRATION OMITTED] you've ever seen the Intel commercials where the workers are wearing clean suits dancing around in a mock factory setting, you should know that those clean suits aren't worn to protect the workers, but to protect the product from the workers. Williams says research shows that the care put into this manufacturing phase accounts for 70 to 80 percent of a computer's energy use over its life cycle. You could, like buying a car with better gas mileage, try to buy an Energy Star Williams says. The problem is, that only addresses 20 to 30 percent of the computer's energy consumption, you haven't done anything to address that larger 70 to 80 percent of consumption that occurs during manufacturing. If you take the strategy of extending the life of the computer--instead of buying a new computer, buy a used one--then you've eliminated the need to manufacture that new computer, at least for a while. energy savings are significant. idea of reusing a computer may bring to mind struggling with a dusty old Commodore 64 that's bogged down by the previous user's data. But that association no longer sticks. Saar Pikar, senior vice president general manager of Ontario, Canada-based CDI Computers, one of the largest providers of refurbished computers to the education market, sold more than 300,000 refurbished computers to school districts in the US, Canada, the UK in 2009 alone. The computers that we sell are usually between six 24 months old, Pikar says. They come from more than 250 sources--leasing brokers, original manufacturers, large Fortune 500 companies. have a lot of life left in them. When a computer arrives at CDI, it is put through a 26-step process during which a team of certified technicians cleans the data from its hard drive, cleans the hardware, removes all stickers identifying marks from the previous owner, then tests audits the unit. Any issues that arise are immediately fixed, bringing the computer back up to its initial factory specifications. Once sold, the unit is returned to the assembly line, where the hardware is again cleaned then upgraded to the specs requested by the customer--at an extra charge, Pikar says, only if those specs require more hardware. Most schools that work with us in the US give us a full software image of their existing computers, Pikar says. We load that image onto the new unit, so when they receive it they just have to plug it in off they go. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".