ACADEMIC RESEARCH ACADEMIC RESEARCH and WRITING and WRITING

Peter Paolucci, Ph.D.Peter Paolucci, Ph.D.

TWO TYPES OF SOURCESTWO TYPES OF SOURCES

POPULARPOPULAR

ACADEMICACADEMICNeither necessarily has truth but one is

more legitimate

See http://www.kyvl.org/html/tutorial/research/infosources.shtml for more examples and (+/-) of both

TWO TYPES OF LIBRARIESTWO TYPES OF LIBRARIES

PUBLICPUBLIC

UNIVERSITYUNIVERSITY

Housing two very different kinds of materials

ACADEMIC PUBLISHINGACADEMIC PUBLISHING1.1. Books Books

2.2. Journals (published monthly)Journals (published monthly)

3.3. Peer review processPeer review processa.a. Sent to several 3Sent to several 3rdrd party experts for scrutiny party experts for scrutiny

b.b. Returned with: rejected, publish with minor Returned with: rejected, publish with minor revs, major revs, or as isrevs, major revs, or as is

ALAN SOKOL ALAN SOKOL

Published an article through peer Published an article through peer review process that was “BS”review process that was “BS”

– Only one article by one journal BUTOnly one article by one journal BUT– Made critical world wonder about the whole Made critical world wonder about the whole

processprocess– Where does truth live?Where does truth live?– What is the relationship between truth and What is the relationship between truth and

legitimacy?legitimacy?

PUBLISHING SCANDALSPUBLISHING SCANDALS

Sokal's Hoax Sokal's Hoax (see next slide)(see next slide)

The Scandal of Poor Medical Research (1/7)The Scandal of Poor Medical Research (1/7)

About the Peer Review ProcessAbout the Peer Review Process

The Abuse of ScienceThe Abuse of Science

INTERNET / LIBRARY INTERNET / LIBRARY KEY DIFFERENCESKEY DIFFERENCES

Librarians standardize Librarians standardize everythingeverything, incl. booleans (and, , incl. booleans (and, or, adj, not) or, adj, not)

butbut Internet search engines Internet search engines

standardize little (they compete)standardize little (they compete)

LIBRARY SCIENCELIBRARY SCIENCE

Is all about standardizationIs all about standardization ISBN numbersISBN numbers Library of CongressLibrary of Congress Standard “subjects”Standard “subjects”

INTERNET SEARCH ENGINESINTERNET SEARCH ENGINES

3 Kinds:3 Kinds:– GenericGeneric (Yahoo)(Yahoo)

– MetaMeta:: search other engines search other engines (Metacrawler)(Metacrawler)

– DedicatedDedicated (Lawcrawler). See(Lawcrawler). See http://searchenginewatch.com/http://searchenginewatch.com/

SEARCH ENGINESSEARCH ENGINES

Each Each – collects collects – filters filters – stores stores – eliminates eliminates – serves data …serves data …

differentlydifferently

See See http://www.learncanada.org/e2nginez/http://www.learncanada.org/e2nginez/

PROBLEMS WITH PROBLEMS WITH SEARCH ENGINESSEARCH ENGINES

Research and promotion = 2 sides of Research and promotion = 2 sides of same coinsame coin

Sometimes what you find has Sometimes what you find has nothing to do with your research nothing to do with your research skillsskills

HOW YOU ARE MANIPULATEDHOW YOU ARE MANIPULATED

Research and promotion Research and promotion = 2 sides = 2 sides of same coinof same coin

What you find has little to do What you find has little to do with your research skills with your research skills

Promotion can be Promotion can be Passive (in the HTML code)Passive (in the HTML code) Active (submitting abstracts or Active (submitting abstracts or

buying ads which are buying ads which are measured in CPMs)measured in CPMs)

TWO APPROACHESTWO APPROACHES

1.1. Searching with purposeSearching with purposetakes takes HUGE amounts of time amounts of time

2.2. ExploratoryExploratory (relying on serendipity) (relying on serendipity)

takestakes STAGGERINGSTAGGERING amounts of time –amounts of time –more than more than you have in any courseyou have in any course

SOLUTIONSSOLUTIONS

The “answer” is The “answer” is NOT NOT in the in the library or on the Internet library or on the Internet ……

It’s It’s

in your head !in your head !

OBJECTIVES OBJECTIVES

1.1. Thoroughness Thoroughness While you’re at it, research more than you needExplore more than is necessaryBring home (copies of) everything you come across

2.2. Accuracy & MeticulousnessAccuracy & MeticulousnessRecord all meta information (aRecord all meta information (author, title, journal, URL, uthor, title, journal, URL,

date, call #, page #, editor, which library)date, call #, page #, editor, which library)Where you wereWhere you wereWhat the date isWhat the date is

OBJECTIVES OBJECTIVES

3.3. Balance & fairnessBalance & fairness Choose a variety of sources, opinions and viewpointsChoose a variety of sources, opinions and viewpoints

Always choose current sources, but older ones are not Always choose current sources, but older ones are not always wrong or outdatedalways wrong or outdated

4.4. ClarityClarity in complexity in complexityRetain paradoxes, dilemmas and inconsistenciesRetain paradoxes, dilemmas and inconsistencies

Don’t oversimplifyDon’t oversimplify

INTENTIONINTENTION

Not always to Not always to narrow downnarrow down your data, but to your data, but to

open upopen up possibilities and possibilities and generate choicesgenerate choices

SCRUTINIZE SOURCESSCRUTINIZE SOURCES

The key isThe key is

TRANSPARENCYTRANSPARENCY

Who wrote it? Credentials?

When? Why?

Are sources used documented and traceable?

EVALUATE SOURCES EVALUATE SOURCES

1.1. Thoroughness Thoroughness

2.2. AccuracyAccuracy

3.3. Balance Balance

4.4. ClarityClarity

= TRANSPARENCY= TRANSPARENCY

PREDICT !PREDICT !

SpeculateSpeculate specifically about specifically about what you what you could find; what find; what you're you're likelylikely to find to find

Even if wrong, it’s better to Even if wrong, it’s better to approach research with approach research with articulated assumptionsarticulated assumptions

KNOWLEDGE / WISDOMKNOWLEDGE / WISDOM

KnowledgeKnowledge = = – Mere data (who, where, what, when)Mere data (who, where, what, when)

WisdomWisdom = data that’s been = data that’s been1.1. scrutinizedscrutinized2.2. labelledlabelled3.3. categorized and clustered (linked relationally and to categorized and clustered (linked relationally and to

other data)other data)

WisdomWisdom = = Why and how Why and how

MAP IT!MAP IT!

Try to locate data in a schematic or Try to locate data in a schematic or map showing its relation tomap showing its relation to

–other data other data –other problems other problems –other concepts other concepts –other ideasother ideas

IMPOSSIBLE TO IMPOSSIBLE TO UNDER ESTIMATEUNDER ESTIMATE … …

The time and trouble it will take The time and trouble it will take (power of bad luck)(power of bad luck)

The power of serendipity The power of serendipity (power of good luck)(power of good luck)

PROCESSPROCESS

PredictPredict Search (gather more than you need)Search (gather more than you need) EvaluateEvaluate Document / recordDocument / record Cluster/group/categorizeCluster/group/categorize

SOME GOOD SOURCES !SOME GOOD SOURCES !

1.1. How to do researchHow to do research

2.2. Advice on Research & WritingAdvice on Research & Writing3.3. Scott Library resourcesScott Library resources (York)(York)

5.5. Style, formatting documentation Style, formatting documentation (Monash U)(Monash U)

6.6. Academic Integrity (avoiding Academic Integrity (avoiding plagiarism)plagiarism)