Choosing and documenting scan sources
Our focus in choosing scanning sources is to select those that identify possible, probable, potential and preferable fundamental changes in:
We believe that most world information is readily available through open sources and that which is hidden behind subscription sites can mostly be deduced. However, we track useful subscription sites for the benefit of our members and use these in client-specific assignments where open sources are insufficient for proper analysis.
For the mainstream, we look for sources that the interest communities themselves use to announce the news. For changes on the social and cultural fringe, we look for voices that express values and ideas bubbling among artists and youth for example. For all scan hits, we seek to ‘get close to the sources of change’.
Here’s where we look:
‘newspapers, websites, blogs, wikis, podcasts, videos, news sites, newsletters; magazines, books, book reviews, presentations, reports, surveys, interviews, seminars, chat rooms, trend observers, advertisers, philosophers, sociologists, management gurus, consultants, researchers, experts, universities’
'Unfortunately, intuitive recognition of a source as useful is not a transferable decision rule. So, in the best tradition of expert systems analyses, we ask ourselves what we are actually doing when we choose sources. To which the shortest possible answer is probably, "identifying opinion leaders." Because our current social construction grants credibility to intellectual adventuring within formal structures, such as science, we label those opinion leaders "experts." As innovative social and cultural ideas and behaviors challenge the status quo with the potential for transformation, they are generally marginalized – hence the usual scanning label of "fringe" for sources on emerging issues among youth, artists, social movements, the underclass, etc.
Our robot, Athena, concentrate on identifying anomalies and patterns from daily scans with a detailed knowledge of where the information resides using proprietary and utility technology to find the best material versus our source categorization.
Athena follows these rules as follows:
She is programmed only to find statements of the future from professional sources. She is self-learning too in many respects and we continue to develop that.
o However, every forecast is curated by our part-time editor and any issues fed back to the developers. Our professional futurist editor is apolitical in that regard.
o The robot has her own unique fake news algorithm built-in. She will not accept fake or hate news. She will accept rumor and controversy but warns the reader.
o She now has the ability for our members and clients to restrict biased sources from PR firms, those accused of cheating and biased reporting, etc.
o She only accepts forecasts that meet our strict relevancy algorithm rules
o She can assess source credibility (TRUST) and members and clients can again refine their search on higher or lower rankled credibility as they wish
o She is also now measuring author intent (this is is a new discovery of ours and unique to us). By counting how many of the provided methods (CLA, SWOT, etc) that the forecasts contain we have mathematically proved that the more methods covered the greater the relevance. Similarly forecasts with no counted intent can be auto rejected. We are working towards that.
o She highlights possible duplicates for removal by the editor
She looks for material that expresses:
New, novel, advance, innovation, renovation, fashion, latest, renew, innovate, newness, fresh,
First, inception, conception, initiative, beginning, debut, onset, birth, infancy, start, dawn, commencement
Idea, notion, belief, apprehension, thought, impression, ideation, point of view, standpoint, theory, prediction
Change, alteration, mutation, permutation, variation, modification, inflection, mood, deviation, turn, inversion, subversion, forecast
Surprise, marvel, astonish, amaze, wonder, stupefy, fascinate, dazzle, startle, take aback, electrify, stun, bewilder, boggle, a wildcard
Opportunity: chance, opening, crisis, juncture, conjuncture, favorable, high time
Threat: future, prospect, anticipation, perspective, expectation, horizon, outlook, look-out, coming, forthcoming, imminent, approaching, fear, uncertainty
A robust scanning strategy will monitor change all along the above curve, and discriminate between the uses and usefulness of data emerging from different points of the curve. When a change is just emerging, and only a few data points exist with which to characterize it, we can only analyze it via a case study approach; changes indicated by limited data points and observations are referred to as “weak signals” of change. As a change matures, more and more data points are available with which to analyze it: we can speak of the change as a variable which is displaying a trend in some direction. The more mature the trend, the more likely it has entered the public arena, and thus attracted issue adherents voicing demands on government.
Therefore, while we may initially tag a trend as having been sourced from an amateur, or the fringe, our task is to strengthen and broaden hits in order to improve source attributes towards professional and expert. If we cannot our system reduces the priority rating we would give to the issue.
What would be measurable or documentable attributes that would help us distinguish among sources, and that would establish sources’ credibility as opinion leaders for their communities of interest?
We ask our researchers to weight these variables for each trend which in turn increases, or decreases, the prioritization of one issue versus another. These ranking systems, in turn, provide a useful sight check of whether our thinking has been sufficiently robust.]
Text in parens above by kind permission of Infinite Futures:
Our framework for determining what should be uploaded is as follows:
Good links have the following attributes:
And our analysis of the links:
Sources and information are deemed to be true and reliable, but Shaping Tomorrow makes no representations to same.
Content management
Fake News
We don't add content from sources identified as 'Fake News'.
We filter each internet domain through a continuously updated and professionally curated list, the aim of which is to preserve the integrity and transparency of information on the internet.
Each is analyzed, looking for extreme biases, lack of transparency and other kinds of misinformation.
The following classification is used:
Here is the list of classified domains.
We believe that anything reliable found in these sources will be quoted elsewhere and that Athena, our robot, will pick these up in the course of her daily work from reputable sources.