Page No ix
·
Possibly, honest astrologers (if
they exist) know that they cannot predict anything with a reasonable certainty
till, astrology thrives because their customers believe so!
Page No x
·
Fuzzy logic?
Page No xi
·
Or “language”- especially one
used in job Advts / Resumes.
Page No xiii
·
I have read somewhere
[DoCoMo?} “Luck is when preparedness meets opportunity”
·
Where you happen to be when
you happen to be.
Page No xv
·
Who may not be even half as
skilled as Buffet!
Page No xl
·
What (patterns) I am trying to search in Résumés?
Job Advt. If I success I will attach some profound scientific meaning.
Page No xli
·
Like critics finding all kinds of “meanings “in the
abstract (absurd?) Paiting’s of Picasso. I believe before his death, he
admitted to have been able to fool the critics!
·
Astrologers
Page No 16
·
Relative positing what we are
trying to show in salary Graphs.
Page No 18
·
Success begets success
calamities come in battalions.
Page No 21
·
Ultimately all the graphs in “Profiles”
will take into account the ‘Co- Professionals” (same industry / same function
/same design level/same end /same age, may be same city.)
Page No 26
·
Yudhisthir answer to yaksha’s
question, “what is the greatest wonder of the world?”
·
Ans: No one think that he is
going to die! Life goes on as if there is no death!!
Page No 29
·
This is (probably?) True of
an all professionals. so it we could get hold of a recent resume of the
recruiter, we could use it as a kind of “benchmark” to compare other resume,
which, he would look upon with interest /respect!
Page No 35
·
Like All anchors
on Indian TV as well.
Page No 38
·
Equally true of Bird Flu.
Page no 44
·
If we capture the resumes of
candidate A for 20 years (one every year-edited / updated), then we have a
sample path. For a million resumes we could get a million “Sample Paths” each
of which could also be alterative sample-path!
·
What all “Design” a person
can acquire over a 20 years period.
Page No 46
·
Salaries & Designations
do not fluctuate up & down randomly. During an executive’s career, salary
generally keeps rising only once a year Design also goes up over 20 years but
much less frequently.
·
Can we complete “how many job
changes before one
Ø reaches a salary of RS.one million
·
a designation of “General
Manager?”
Page No 47
·
Touching the sides of the
square? 22/7 on 7/22?
Page No 53
·
Once again: Yudhisthir’s
answer to yaksha! I Cannot [Possibly] die despite seeing hundreds die every
day! I believe, this is nature s gateway of protecting us from horrendous
mantel depression.
Page No 54
·
This too, shall pass! What will remain is
the “steady State condition - the average! Nature hates extremes.
·
Death of a loved one at a young age - would
fall in this category.
Page No 55
·
But then that feeling is what sustains an extend hope for a
better tomorrow.
Page No 56
·
One can only decide with the info
available at the point of decision which is limited in its quantity &
quality at that moment.
Page No 58
·
If we plot “career Track”
graphs of a million executives, over a 20 year period (of their career) would
these end-up looking very similar?
·
What is the time frame for
such “eventuality?”
·
Can we (someday) find a method
to differentiate between “NOISE” & “INFO” contain end in a resume? Can we work
backwards say “In resume whatever is more Radom-low probability is a “noise”
keywords having low probability?
Page No 60
·
Most of this email resumes pouring
into the mail boxes, are “noise”. Trick is to find the “Needle!”
Page No 61
·
Recruiters (HR Mgrs.), Possibly spend 6
hrs./day reading “Resume” (which keep pouring at a rate faster than a recruiter’s
ability/speed to read thru). Maybe, they too believe that “next” resume will be
the GEM they are looking for!
Page No 62
·
In presenting “Profiles”
graphically, we are trying to distil resume info and present it in easily
digestible/graspable form.
Page No 67
·
My portfolio consists of only
L&T & ultratech shares which I look up every evening on TV then forget!
·
I have cut down from &
papers of just 1
Page No 72
·
Ray Kurzweil has developed a “paraphrasing”
software which can ‘rewrite/ recompose” poetry which reads like an original
literary composition.
·
Also a resume?
Page no 74
·
I suppose a frequency distribution analysis of sentences
contained if any resumes or jobadvts will reveal some pattern.
Page No.76
·
Same can be said about the (near)
dead, ancient languages of India, viz: Sanskrit, Magdhi, Ardh Magdhi, prakrut
etc.
Page No 96
·
Let us treat “jobsites” as a “species”
(on the web) Google may wipe these out within next 5 years (nowhere near
infinity) are Because Google’s database & search engines evolving rapidly.
Page No. 98
·
In “profiles “we are using “Mean
[AVE].” and +16 (68%)
Page no. 104
·
Read Book
·
“Long Tail”
Page No 105
·
May be we should follow this
practice in our “profiles” while computing MEAN (AVE) of the dataset. There can
be no catastrophY.
Page No 108
·
Indian rupees remained insulated
·
Eg: last super volcano erupted 75000 years
ago! Hence a rare event.
Page No 115
Could this happen to “Function Profiles” which
are based on “presence” of some high frequency, keywords in a person resume?
Over a period, jobseekers will possibly figure out that including /
incorporating such keywords in their resumes will get them a high “Raw score”
and consequently a higher “Percentile score!” So, every jobseeker may start “doctoring”
his/her resume to incorporate such keywords - a somewhat easy task. But then,
during interview (using IIT), they will face barrage of questions-which they
cannot answer!
Page No 120
·
Same thing far worse can
still happen!
Page No 142
·
Obviously, to get a good
looking “Normal Distribution” curve, we need both, many “Low score” and equally
large “High score” resumes - only excluding “Rare’s” at either end.
Page no 144
·
For once Nassem is so wrong!
Warren just gifted away his 40+billion estate to Bill gates charity and so did
bill gates himself!
Page no 145
·
So what? I suppose everybody
knows that for every winner, hare are may be 10 losers!
Page no 152
·
Like a set of resumes having raw scores
between 50’s and 60s What would such distribution curve look like?
Page no 158
·
Read my note: “Horoscope and
other equally fictitious stories”
·
Some of our “recommendations”
(asking candidates to apply to ABC/ XYZ companies) are bound to prove correct!
Page no 159
·
We use “Birthdates” to
eliminate duplicate resumes.
Page no 162
·
See my notes on “expert
systems & some rules [if/then] framed by me.
Page No 175
·
Self-fulfilling prophesy is
behind my idea to introduce following counters. This resume viewed 64 time.
·
Ditto with job Advs.
Page no 176
What I plan to introduce thru “profiles
created/ co in stacked” OFFLINE “thru enterprise version of guru mine/guru
search.
Page no 177
This is my idea behind “raw
score”/percentile /mean/ standard deviation etc.in profile guruohs.lend an aura
of precision /scientific rigout/credibility.
Page No 179
·
So, I must not give up I must
pushing the envelope the daily relent Lesley.
Page No 183
·
This is what we plan to do, by making
available to HR managers,3 function/ skill graphs for the SAME candidate, each
showing his raw score and relative position- percentile.
·
We are talking of the existence of a
combination of 3 skills in a person same time.
Page no 185
·
Here are only 2 distinctly
different “states” in which a person could belong.in profiles “we are trying to
place a person, into 3 different “states [skills], simultaneously!
Page No 191
·
There is a likelihood of such a situation when our “Guru
search” presents 15 candidates, each with 3 “skill Grabs-and each graph with a
different” Raw score different “percent score” different population-size.
Page no 193
Time axis once-a-month plotting of percentile.
Page no 196
“Keywords “contained in his resume.
Page No 198
·
I do hope Recruitment mgrs. Use
“Representativeness heuristics” while looking at graphical profiles of
candidates- and make their “choices”
Page No 201
·
In profiles Y axis, shows
“percentages %”
Page No 240
·
But having invested time in
an idea you must at least “test” it in the market before changing your mind.
Page No 244
·
In “profiles” skill/ function
graphs, all those whose “raw scores” are higher than the “Mean (average)”,
would find their own “self- rating”, vindicated!
·
Such candidates might become
the most vociferous “advocates” of the Profiles! They might become our best
“salesman”!
Page No 248
An acute case of depression.
Page No 262
In profiles, we are capturing Keyword’s “embedded” in a
resume and making them “visible” (in IIT box). The graphs are themselves made
“narrative” & “tangible.”
